Jobs at Amgen

Job Description ABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today. ABOUT THE ROLE Role Description: As the Senior Associate Data Scientist at Amgen, you will be responsible for developing and deploying advanced machine learning models. This role will support the development of statistical, Bayesian, causal, and machine learning models that enhance forecasting capabilities and quantify uncertainty to guide decision-making across the company. The position is well suited to a curious and collaborative problem solver who is excited about applying forecasting methods, complex datasets, and modern analytical tools to build decision-support solutions that inform planning and business decision-making. Roles & Responsibilities: • Analyze large, complex datasets using statistical modeling, forecasting, and analytics techniques to generate insights that support business decision-making. • Support the development of simulation and scenario-analysis capabilities to better understand the data • Contribute across the modeling lifecycle, including business problem framing, exploratory data analysis, feature engineering, model development, validation, deployment support, monitoring, and explainability. • Collaborate with senior team members to evaluate and apply new tools and methodologies in forecasting, data science, and AI to business problems. • Communicate analytical findings and model results clearly to technical and non-technical stakeholders. • Ensure models are trained with the latest data and meet the SLA expectations • Work with a global cross functional team on the AI tool’s road map • Work in technical teams in development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics. • Utilize technical skills such as hypothesis testing, machine learning and retrieval processes to apply statistical and data mining techniques to identify trends, create figures, and analyze other relevant information. • Perform exploratory and targeted data analyses using descriptive statistics and other methods. • Model/analytics experiment and development pipeline leveraging MLOps. • Collaborate with technical teams to translate the business needs into technical specifications, particularly focusing on AI-driven automation and insights. • Develop and integrate custom applications, intelligent dashboards, and automated workflows that incorporate AI capabilities to enhance decision-making and efficiency. Basic Qualifications: • Master’s OR Bachelor’s degree in computer science, statistics or STEM majors with a minimum of 4 years and maximum of 7 years of Information Systems experience. Must-Have Skills • Strong Python and SQL skills for data analysis, statistical modeling, and automation. • Hands-on experience with machine learning, predictive analytics, and forecasting models. • Solid knowledge of statistics, including hypothesis testing, descriptive statistics, and experimental analysis. • Experience across the end-to-end model lifecycle: data exploration, feature engineering, model development, validation, deployment, monitoring, and explainability. • Ability to work with large and complex datasets using data-mining and analytical techniques. • Familiarity with MLOps practices, including model pipelines, versioning, deployment support, retraining, and performance monitoring. • Experience building simulation or scenario-analysis models. • Ability to translate business problems into technical requirements and analytical solutions. • Experience developing AI-enabled dashboards, automated workflows, or data applications. • Strong stakeholder communication skills—able to explain insights and model outcomes to both technical and business audiences. • Experience working in cross-functional, global technical teams. Good-to-Have Skills: • Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow); Experience in DevOps tools (e.g., Docker, Kubernetes, CI/CD) • Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn) • Outstanding analytical and problem-solving skills; Ability to learn quickly; Excellent communication and interpersonal skills • Experience with data engineering and pipeline development • Knowledge of NLP techniques for text analysis and sentiment analysis • Experience in analyzing time-series data for forecasting and trend analysis • Experience with AWS, Azure, or Google Cloud • Experience with Databricks platform for data analytics and MLOps Professional Certifications : • Any AWS Developer certification (preferred) • Any Python and ML certification (preferred) Soft Skills: • Initiative to explore alternate technology and approaches to solving problems. • Skilled in breaking down problems, documenting problem statements, and estimating efforts. • Excellent analytical and troubleshooting skills. • Strong verbal and written communication skills • Ability to work effectively with global, virtual teams • High degree of initiative and self-motivation. • Ability to manage multiple priorities successfully. • Team-oriented, with a focus on achieving team goals EQUAL OPPORTUNITY STATEMENT Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

Senior Software Engineer, Full Stack — Decision Intelligence ABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today. The opportunity Amgen’s AI & Data Science team is building decision-intelligence products that help teams make faster, more defensible decisions under uncertainty. We are seeking a Senior Software Engineer, Decision Intelligence to join the Forecasting & Decision Intelligence team, within the AI & Data organization. This role will develop cutting edge scenario-planning capabilities, while creating reusable foundations for forecasting, simulation, optimization, and AI-assisted decision products across the enterprise. We are seeking a Full-Stack Engineer who can own meaningful product experiences end-to-end. You will build the interfaces people use to configure, launch, monitor, compare, and understand complex scenarios, as well as the APIs, data integrations, and execution services that make those experiences trustworthy. What you will do • Design, build, deploy, and operate end-to-end decision-support products across frontend, backend, data, and workflow layers. • Create intuitive planner experiences for configuring scenarios, managing assumptions, launching and monitoring, comparing outcomes, and understanding uncertainty and trade-offs. • Build responsive, accessible React/TypeScript user interfaces and reusable frontend components for scenario setup, results visualization, and decision workflows. • Design and implement production APIs, backend services, data integrations, and execution workflows for forecasting, simulation, optimization, and AI-assisted decision products. • Work closely with product managers, planners, data scientists, and adjacent engineering teams to translate ambiguous business needs into simple, valuable releases. • Lead substantial workstreams independently, provide thoughtful code reviews, and mentor developing engineers. Basic qualifications • Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience. • 10+ years of professional software-engineering experience, including ownership of complex production applications or major end-to-end capabilities. • Strong full-stack engineering experience, including modern frontend development with React and TypeScript and backend API development with Python or another modern server-side language. • Experience designing usable, data-rich web applications in partnership with product, design, and business stakeholders. • Experience with relational SQL and data-intensive applications, including integration with warehouse, lakehouse, or operational data systems. • Experience with asynchronous processing, queues, workflow engines, or resilient patterns for long-running workloads. • Experience with cloud deployment, containers, CI/CD, automated testing, and production troubleshooting. • Demonstrated commitment to code quality, accessibility, observability, documentation, and operational ownership. Preferred qualifications • Experience with FastAPI, Databricks, Spark, Kubernetes, modular frontend architectures, or comparable technologies. • Experience building interactive visualizations and comparison workflows for analytical, operational, financial, or planning users. • Experience embedding statistical models, optimization engines, simulation, or machine-learning capabilities into production applications. • Experience with API and data-contract versioning, enterprise identity and access management, and secure integrations. • Experience in supply chain, manufacturing, healthcare, finance, or another complex operational domain. • Familiarity with AI-assisted product experiences and appropriate grounding, evaluation, and human-review controls.

Senior Software Engineer, Full Stack — Decision Intelligence ABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today. The opportunity Amgen’s AI & Data Science team is building decision-intelligence products that help teams make faster, more defensible decisions under uncertainty. We are seeking a Senior Software Engineer, Decision Intelligence to join the Forecasting & Decision Intelligence team, within the AI & Data organization. This role will develop cutting edge scenario-planning capabilities, while creating reusable foundations for forecasting, simulation, optimization, and AI-assisted decision products across the enterprise. We are seeking a Full-Stack Engineer who can own meaningful product experiences end-to-end. You will build the interfaces people use to configure, launch, monitor, compare, and understand complex scenarios, as well as the APIs, data integrations, and execution services that make those experiences trustworthy. What you will do • Design, build, deploy, and operate end-to-end decision-support products across frontend, backend, data, and workflow layers. • Create intuitive planner experiences for configuring scenarios, managing assumptions, launching and monitoring, comparing outcomes, and understanding uncertainty and trade-offs. • Build responsive, accessible React/TypeScript user interfaces and reusable frontend components for scenario setup, results visualization, and decision workflows. • Design and implement production APIs, backend services, data integrations, and execution workflows for forecasting, simulation, optimization, and AI-assisted decision products. • Work closely with product managers, planners, data scientists, and adjacent engineering teams to translate ambiguous business needs into simple, valuable releases. • Lead substantial workstreams independently, provide thoughtful code reviews, and mentor developing engineers. Basic qualifications • Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience. • 10+ years of professional software-engineering experience, including ownership of complex production applications or major end-to-end capabilities. • Strong full-stack engineering experience, including modern frontend development with React and TypeScript and backend API development with Python or another modern server-side language. • Experience designing usable, data-rich web applications in partnership with product, design, and business stakeholders. • Experience with relational SQL and data-intensive applications, including integration with warehouse, lakehouse, or operational data systems. • Experience with asynchronous processing, queues, workflow engines, or resilient patterns for long-running workloads. • Experience with cloud deployment, containers, CI/CD, automated testing, and production troubleshooting. • Demonstrated commitment to code quality, accessibility, observability, documentation, and operational ownership. Preferred qualifications • Experience with FastAPI, Databricks, Spark, Kubernetes, modular frontend architectures, or comparable technologies. • Experience building interactive visualizations and comparison workflows for analytical, operational, financial, or planning users. • Experience embedding statistical models, optimization engines, simulation, or machine-learning capabilities into production applications. • Experience with API and data-contract versioning, enterprise identity and access management, and secure integrations. • Experience in supply chain, manufacturing, healthcare, finance, or another complex operational domain. • Familiarity with AI-assisted product experiences and appropriate grounding, evaluation, and human-review controls.

Description Join Amgen's Mission to Serve Patients If you feel like you’re part of something bigger, it’s because you are. At Amgen, our shared mission—to serve patients—drives all that we do. It is key to our becoming one of the world’s leading biotechnology companies. We are global collaborators who achieve together—researching, manufacturing, and delivering ever-better products that reach over 10 million patients worldwide. It’s time for a career you can be proud of. Associate Data Scientist Live What will you do? Amgen is seeking a highly skilled and motivated Data Analyst with understanding in product and patient complaints to join our dynamic team. The ideal candidate will possess a unique blend of analytical process, healthcare industry knowledge, and a passion for improving patient outcomes through data-driven insights. In this vital role we are seeking a highly skilled and detail-oriented Data Analyst to join our dynamic team. This role is pivotal in ensuring that our products meet the highest standards of quality and that patient complaints are thoroughly analyzed and addressed. The ideal candidate will possess a strong background in data analysis, excellent communication skills, and a passion for improving patient outcomes and product quality. • Collect, organize, and analyze data related to product performance (e.g., APRs) and patient complaints. • Ensure data integrity, accuracy, and accessibility for further analysis. • Utilize statistical software and data visualization tools to interpret and present findings. • Identify trends, patterns, and insights from large datasets to inform decision-making processes. • Prepare comprehensive reports summarizing analysis results, including actionable recommendations. • Maintain accurate and up-to-date documentation of all data analysis activities. • Ensure compliance with regulatory requirements and company policies in all documentation and reporting. • Collaborate with cross-functional teams to develop and implement quality improvement initiatives based on data analysis findings. • Provide insights and support for product complaint teams to enhance product quality and patient experience. • Present data analysis results and recommendations to management and other stakeholders. • Foster strong relationships with external and internal partners. • Data Cleaning: Ensuring data integrity by identifying and rectifying errors, inconsistencies, and duplications. • Database Management: Storing and organizing data in databases or data warehouses for easy access and analysis. • Diagnostic Analysis: Investigating the root causes of specific issues, such as recurring product defects or common patient complaints. • Visualization: Developing charts, graphs, and dashboards to present data in a more understandable and impactful manner. Win What we expect of you? We are all different, yet we all use our unique contributions to serve patients. Basic Qualifications: • Bachelor’s degree and 1 to 3 years of experience in data analyst, preferably within the healthcare, biotech, medical devices or pharmaceutical industry and with one or more analytic software tools or languages (e.g., Data Bricks, Salesforce, SAS, SQL, Python) and experience with data visualization tools like Square Two (S2), Spotfire, BioConnect, Tableau, Power BI, Smartsheet, or similar, OR • Any Python, SA, Salesforce or SQL certification (preferred) • Fluency in verbal and written English to be able to understand & articulate technical concepts Preferred Qualifications: • Strong analytical and problem-solving skills with the ability to interpret complex data sets. • Excellent written and verbal communication skills. • Ability to work independently and collaboratively in a fast-paced environment. • Attention to detail and a commitment to quality and accuracy. • Knowledge of regulatory requirements and quality management systems (e.g., ISO 13485, FDA regulations) is a plus. • Proactive and self-motivated with a strong sense of responsibility. • Adaptable and able to manage multiple priorities effectively. • Patient-centric mindset with a commitment to improving healthcare outcomes. Thrive What can you expect of us? • As we work to develop treatments that take care of others, we also work to care for our teammates’ professional and personal growth and well-being. • Diverse and inclusive community of belonging, where teammates are empowered to bring ideas to the table and act • Vast opportunities to learn and move up and across our global organization • In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards. Apply now for a career that defies imagination In our quest to serve patients above all else, Amgen is the first to imagine, and the last to doubt. Join us. careers.amgen.com Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Level: Associate (L3) Role: Marketing Investment Optimization – Investment Analytics MIO OVERVIEW The Marketing Investment Optimization (MIO) vertical at Amgen is responsible for enabling data‑driven, decision‑grade marketing investment decisions across brands, channels, and portfolios. MIO brings together Investment Analytics (IA), Media Analytics (MA), and Marketing Science Operations (MSO) to measure effectiveness, quantify incrementality, and optimize marketing investments. MIO focuses on marketing mix modelling (MMx), Experimentation and Causal Measurement, Optimization, Media and Campaign analytics, Scenario Planning, ensuring that marketing dollars are allocated to maximize business impact. The team partners closely with Brand Marketing, GCC/Agencies, CD&A, and MSO to translate complex analytics into actionable investment decisions. Role Summary The Associate – Investment Analytics role is an entry‑level analytics position within the Investment Analytics team. This role is ideal candidates who are excited about applying analytical thinking, structured problem solving, and data skills to real‑world business questions. The team will provide structured learning and on‑the‑job exposure. What matters most is curiosity, critical thinking, and a strong learning mindset. LIVE | WHAT YOU WILL DO As an Associate, you will work under guidance from Senior Associates and Managers to support analytical deliverables and build strong foundations in applied analytics. You will: • Develop and apply advanced statistical models that help clients understand dynamic business issues. • Leverage analytic techniques to use data to guide decision-making. • Design custom analyses in R, Python and Excel to investigate and inform business needs. • Assist in preparing analysis summaries, documentation, and presentation materials. • Collaborate with team members to meet project timelines and quality standards and actively communicate project status updates. • Engage in ongoing learning to develop industry knowledge, and technical capabilities. BASIC QUALIFICATIONS • Bachelor's (3 to 6 Yrs) or master's (2 to 4 Yrs) degree required in any discipline with strong record of academic success in quantitative and analytic coursework such as operations research, applied mathematics, management science, data science, statistics, econometrics or engineering. • Experience in any analytical, data, or problem‑solving role. • Strong SQL skills and hands‑on experience with Python or R. Preferred Qualifications • Demonstrated ability to perform structured QA and validation. • Experience working with time‑series and investment data. • Exposure to Marketing Mix Modelling (MMx) or econometric analysis. • Experience supporting analytics in pharma, healthcare, or regulated environments. • Strong communication skills with the ability to collaborate closely with Senior Associates to deliver high‑quality analytical outputs.

Level: Associate (L3) Role: Marketing Investment Optimization – Investment Analytics MIO OVERVIEW The Marketing Investment Optimization (MIO) vertical at Amgen is responsible for enabling data‑driven, decision‑grade marketing investment decisions across brands, channels, and portfolios. MIO brings together Investment Analytics (IA), Media Analytics (MA), and Marketing Science Operations (MSO) to measure effectiveness, quantify incrementality, and optimize marketing investments. MIO focuses on marketing mix modelling (MMx), Experimentation and Causal Measurement, Optimization, Media and Campaign analytics, Scenario Planning, ensuring that marketing dollars are allocated to maximize business impact. The team partners closely with Brand Marketing, GCC/Agencies, CD&A, and MSO to translate complex analytics into actionable investment decisions. Role Summary The Associate – Investment Analytics role is an entry‑level analytics position within the Investment Analytics team. This role is ideal candidates who are excited about applying analytical thinking, structured problem solving, and data skills to real‑world business questions. The team will provide structured learning and on‑the‑job exposure. What matters most is curiosity, critical thinking, and a strong learning mindset. LIVE | WHAT YOU WILL DO As an Associate, you will work under guidance from Senior Associates and Managers to support analytical deliverables and build strong foundations in applied analytics. You will: • Develop and apply advanced statistical models that help clients understand dynamic business issues. • Leverage analytic techniques to use data to guide decision-making. • Design custom analyses in R, Python and Excel to investigate and inform business needs. • Assist in preparing analysis summaries, documentation, and presentation materials. • Collaborate with team members to meet project timelines and quality standards and actively communicate project status updates. • Engage in ongoing learning to develop industry knowledge, and technical capabilities. BASIC QUALIFICATIONS • Bachelor's (3 to 6 Yrs) or master's (2 to 4 Yrs) degree required in any discipline with strong record of academic success in quantitative and analytic coursework such as operations research, applied mathematics, management science, data science, statistics, econometrics or engineering. • Experience in any analytical, data, or problem‑solving role. • Strong SQL skills and hands‑on experience with Python or R. Preferred Qualifications • Demonstrated ability to perform structured QA and validation. • Experience working with time‑series and investment data. • Exposure to Marketing Mix Modelling (MMx) or econometric analysis. • Experience supporting analytics in pharma, healthcare, or regulated environments. • Strong communication skills with the ability to collaborate closely with Senior Associates to deliver high‑quality analytical outputs.

Role: Associate - AI/ML Innovation Engineer Job Description: ABOUT AMGEN At Amgen, if you feel like you're part of something bigger, it's because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do. Since 1980, we've helped pioneer the world of biotech in our fight against the world's toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. As a member of the Amgen team, you'll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives. Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you'll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career. ABOUT THE ROLE Role Description: As an AI/ML Innovation Associate, you will help build next-generation AI-powered platforms that transform how commercial, contracting, and patient access strategies are designed and executed across the US Value & Access organization. Our AI portfolio includes AI copilots, intelligent contract systems, anomaly detection engines, and real-time decision platforms that directly impact how Amgen serves patients and partners. In this role, you will work on production-grade AI systems, contributing to the development of scalable, intelligent solutions that integrate structured and unstructured data, power decision-making, and deliver measurable business impact. You will collaborate with senior data scientists, engineers, and business partners to bring cutting-edge GenAI, LLM, and ML solutions from prototype to production. Roles & Responsibilities: You will contribute to one or more of the following high-impact areas: • AI Copilots & Agents: Build LLM-powered assistants, implement prompt engineering, Retrieval-Augmented Generation (RAG) pipelines, and agentic workflows and related applications • Intelligent Document & Contract AI: Extract, classify, and query insights from unstructured documents (contracts, policies, SOPs); build NLP pipelines for semantic search and summarization • Data & AI Platforms: Work on data ingestion, transformation, and feature engineering pipelines; contribute to scalable AI/ML infrastructure • Real-time AI Systems: Build APIs, dashboards, and backend services that power AI-driven insights for end users • Analytics & Decision Engines: Develop anomaly detection models (e.g., claims, pricing, Gross-to-Net); build forecasting and optimization models to support commercial decisions • Collaborate with cross-functional technical teams to translate business needs into technical specifications, focusing on AI-driven automation and insights • Participate in code reviews, design discussions, and adopt best practices across MLOps and software engineering Functional Skills: Must-Have Skills: • Strong programming skills in Python, PySpark, and SQL • Solid understanding of Data Structures & Algorithms, OOP, and System Design fundamentals • Hands-on experience with core Machine Learning techniques (Regression, Classification, Clustering) • Working knowledge of NLP fundamentals (tokenization, embeddings, transformers) • Exposure to LLMs (OpenAI, HuggingFace, Anthropic, etc.) and prompt engineering / GenAI workflows • Experience with data manipulation libraries (Pandas, NumPy) and working with both structured and unstructured data • Familiarity with REST APIs and backend development basics • Mandatory hands-on experience with 2–3 real AI/ML projects • AI/GenAI: LLM-based chatbot with RAG (document Q&A), AI summarization tools, or agent-based multi-step reasoning systems • Engineering: Deployed ML models (API or web app), data pipelines (ETL/ELT) Good-to-Have Skills: • Experience with RAG pipelines and vector databases (FAISS, Pinecone, Chroma, Weaviate) • Hands-on experience with LangChain, LlamaIndex, or agent frameworks (AutoGen, CrewAI) • Exposure to MLOps tools (Docker, CI/CD, MLflow, Kubeflow, Airflow) • Knowledge of time-series forecasting and anomaly detection techniques • Frontend basics (Streamlit, React) for building dashboards and demos • Familiarity with cloud platforms (AWS, Azure, or GCP) • Experience with Databricks for data analytics and ML workflows • Foundational understanding of the US pharmaceutical ecosystem, relevant datasets (e.g., claims, prescription data), and Patient Support Services offerings Professional Certifications (optional): • Any AWS / Azure / GCP certification (preferred) • Any Python, Machine Learning, or GenAI certification (preferred) Soft Skills: • Initiative to explore new technologies and alternate approaches to solving problems • Strong analytical and troubleshooting skills with the ability to break down complex problems • Excellent verbal and written communication skills • Ability to work effectively with global, virtual, cross-functional teams • High degree of curiosity, initiative, and self-motivation • Team-oriented mindset with a focus on collective goals • Ability to manage multiple priorities and learn quickly in a fast-paced environment Basic Qualifications: - Bachelor's or master’s degree in computer science, Artificial Intelligence, Data Science, Statistics, Engineering, or other STEM majors - 1–3 years of hands-on experience in AI/ML, data science, or software engineering roles - Demonstrated portfolio of AI/ML projects (GitHub, publications, or production deployments) EQUAL OPPORTUNITY STATEMENT Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

Job Description The role is responsible for designing, developing, and maintaining software solutions for Research scientists. Additionally, it involves automating operations, monitoring system health, and responding to incidents to minimize downtime. You will join a multi-functional team of scientists and software professionals that enables technology and data capabilities to evaluate drug candidates and assess their abilities to affect the biology of drug targets. This team implements scientific software platforms that enable the capture, analysis, storage, and reporting for our Large Molecule Discovery Research team (Design, Make, Test and Analyze processes). The team also interfaces heavily with teams supporting our in vitro assay management systems and our compound inventory platforms. The ideal candidate possesses experience in the pharmaceutical or biotech industry, strong technical skills, and full stack software engineering experience (spanning SQL, back-end, front-end web technologies, automated testing). Roles & Responsibilities: • Work closely with product team, business team including scientists, and other stakeholders • Analyze and understand the functional and technical requirements of applications, solutions and systems and translate them into software architecture and design specifications • Design, develop, and implement applications and modules, including custom reports, interfaces, and enhancements • Develop and execute unit tests, integration tests, and other testing strategies to ensure the quality of the software • Conduct code reviews to ensure code quality and adherence to best practices • Create and maintain documentation on software architecture, design, deployment, disaster recovery, and operations • Provide ongoing support and maintenance for applications, ensuring that they operate smoothly and efficiently • Stay updated with the latest technology and security trends and advancements Basic Qualifications and Experience: • Master's or Bachelor’s degree with 5 - 8 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field OR Preferred Qualifications and Experience: • 1+ years of experience in implementing and supporting biopharma scientific software platforms Functional Skills: Must-Have Skills: • Proficient in Python programming language or java full stack programming language • Proficient in at least one JavaScript UI Framework (e.g. ExtJS, React, or Angular) • Proficient in SQL (e.g. Oracle, PostgreSQL, Databricks) Good-to-Have Skills: • Experience with big data technologies (e.g., Spark, Databricks, Kafka) • Experience with event-based architecture and serverless AWS services such as EventBridge, SQS, Lambda or ECS. • Experience with Benchling • Hands-on experience with Full Stack software development • Strong understanding of software development methodologies, mainly Agile and Scrum • Working experience with DevOps practices and CI/CD pipelines • Experience of infrastructure as code (IaC) tools (Terraform, CloudFormation) • Experience with monitoring and logging tools (e.g., Prometheus, Grafana, Splunk) • Experience with leveraging the use of AI-assistants (e.g. GitHub Copilot) to accelerate software development and improve code quality Professional Certifications (preferred): • AWS Certified Cloud Practitioner Soft Skills: • Excellent problem solving, analytical, and troubleshooting skills • Strong communication and interpersonal skills • Ability to work effectively with global, virtual teams • High degree of initiative and self-motivation • Ability to learn quickly & work independently • Team-oriented, with a focus on achieving team goals • Ability to manage multiple priorities successfully • Strong presentation and public speaking skills

Sr. Data Scientist – Data Sciences & Artificial Intelligence ABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases and make people’s lives easier, fuller, and longer. We discover, develop, manufacture, and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting edge of innovation, using technology and human genetic data to push beyond what is known today. ABOUT THE ROLE Role Description Global Supply Chain (GSC) is accountable for orchestrating end-to-end supply chain strategies and operations that ensure reliable, timely delivery of medicines to patients — powered by data, innovation, and enterprise-wide collaboration. As part of our team expansion at Amgen India (AIN), GSC is seeking an experienced applied AI Data Scientist to join our team. As a Senior AI Data Scientist, you will be responsible for designing, developing, and deploying complex software applications on clinical and commercial supply chain processes. This role will be actively collaborating with a wide range of business leaders, designing and implementing sophisticated analytical models. You will work closely with cross-functional teams to deliver high-quality, scalable, and maintainable solutions. ROLES & RESPONSIBILITIES Responsibilities will include, but are not limited to: Rapid prototyping and AI solution development: Quickly translate business concepts, scientific questions, and product ideas into working AI prototypes, production-ready code, and scalable digital capabilities. AI/ML, Generative AI, and advanced modeling delivery: Develop innovative AI/ML solutions using Large Language Models, Generative AI, foundation models, supervised and unsupervised learning, and other advanced modeling techniques to support supply chain decision-making and automation. AI application integration and automation: Integrate AI capabilities into Global Supply Chain applications, APIs, workflows, assistants, copilots, and automation platforms using context engineering, tool integration, and emerging approaches such as Model Context Protocol to enable real-time intelligence, productivity, operational efficiency, and improved user experience. End-to-end AI and data science ownership: Own complex AI, data science, and decision-support solutions from problem framing through prototype, validation, deployment, and stabilization, managing scope, risks, dependencies, timelines, technical tradeoffs, and measurable outcomes such as cycle time, forecast quality, data quality, and operational efficiency. Technical documentation, quality, and problem-solving: Create clear documentation for prototypes and solutions, including design choices, data flows, AI workflows, assumptions, limitations, and key implementation details; identify and resolve technical challenges effectively. Technology evaluation and learning agility: Stay current with emerging AI technologies, frameworks, industry trends, and engineering practices, demonstrating the ability to assess options, conduct due diligence, and make informed technology recommendations based on business value, technical fit, and implementation impact. Product and module ownership: Develop a strong understanding of the overall product, its modules, dependencies, AI components, and user workflows while serving as a technical expert for assigned components or solution areas. Cross-functional collaboration and stakeholder partnership: Work closely with product teams, business teams, technology teams, architecture teams, AI platform teams, data teams, stakeholders, and subject-matter experts to deliver practical, scientific, data-driven solutions aligned with enterprise standards. Requirements translation and Agile delivery: Synthesize business, scientific, and technical inputs into prioritized features, user stories, acceptance criteria, and delivery plans; actively participate in Agile ceremonies, including sprint planning, backlog refinement, estimation, demos, and retrospectives. Innovation and continuous improvement: Contribute to a culture of accountability, continuous learning, innovation, technical curiosity, rapid experimentation, platform-first thinking, and high-quality delivery. Must-Have Skills • Experience developing and applying AI/ML, Generative AI, analytics, automation, BI, and data visualization solutions to supply chain use cases, using techniques such as Large Language Models, foundation models, predictive modeling, feature engineering, and exploratory data analysis to solve complex business problems. • Hands-on experience building GenAI and LLM-based applications, including chatbots, copilots, Retrieval-Augmented Generation pipelines, vector database integration, prompt-driven workflows, context-aware AI systems, and enterprise application or workflow integration. • Experience with AI orchestration and application frameworks such as LangChain, LangGraph, or similar tools. • Strong understanding of AI agent architectures, orchestration patterns, Responsible AI, model validation principles, and enterprise AI governance. • Strong hands-on development skills for AI and data science solutions, including Python, AI/ML and data science libraries, APIs, SQL/NoSQL databases, data pipelines, and modern application development practices. • Prior exposure to pharma, life sciences, or regulated AI environments preferred; familiarity with GxP, HIPAA, or related compliance expectations is a plus. Soft Skills • Excellent problem-solving, storytelling, communication, and interpersonal skills, with the ability to explain technical concepts in clear business language. • Strong verbal and written communication skills, with attention to detail, organization, documentation, and presentation abilities. • Ability to bridge technical and non-technical teams, synthesize stakeholder inputs, and translate data and AI insights into meaningful business recommendations. • Skilled in breaking down complex problems, documenting problem statements, estimating effort, assessing technology tradeoffs, and analyzing implementation impact. • Independent, self-motivated, organized, and able to manage multiple priorities in fast-paced, time-sensitive environments. • Strong collaboration, facilitation, and team-working skills, including experience working effectively with global virtual teams. • Demonstrated ability to deliver results across Agile projects, adapt to setbacks, explore alternative approaches, and maintain persistence through completion. • Awareness of industry trends, emerging technologies, and new approaches for solving complex business problems.

Role Description We are seeking an experienced Specialist Software Engineer to lead the design, development, deployment, and operation of scalable enterprise software solutions. This role combines full-stack development, cloud engineering, DevOps, application security, system reliability, and AI-enabled solution development. The ideal candidate has strong hands-on experience with React, Vite, FastAPI, Python, TypeScript or JavaScript, APIs, microservices, AWS, containerization, CI/CD, DevSecOps, and production operations. The role will provide technical leadership, establish engineering standards, mentor developers, and collaborate with product, design, data, quality, cybersecurity, and platform teams. Roles and Responsibilities • Lead the design, development, testing, deployment, and support of complex enterprise software solutions. • Own software initiatives from requirements and architecture through production deployment and operational support. • Manage technical scope, risks, dependencies, estimates, and delivery timelines. • Translate business requirements into scalable, secure, resilient, and maintainable solutions. • Develop responsive front-end applications using React, Vite, and TypeScript. • Develop back-end services, RESTful APIs, integrations, and data-access components using Python and FastAPI. • Build cloud-native solutions using microservices, serverless technologies, containers, APIs, and event-driven patterns. • Integrate applications with enterprise systems, identity platforms, databases, cloud services, and third-party solutions. • Develop AI-enabled applications using machine learning, Generative AI, LLMs, and Retrieval-Augmented Generation where appropriate. • Collaborate with data scientists and ML engineers to integrate predictive models and AI capabilities into applications. • Establish reusable design patterns, coding standards, engineering practices, and technical documentation. • Lead architecture, design, and code reviews to ensure quality, security, performance, and maintainability. • Apply secure software-development practices and integrate security testing into the software-development lifecycle. • Use tools such as Veracode, Snyk, SonarQube, Checkmarx, Fortify, or equivalent platforms to identify and remediate security and code-quality findings. • Implement unit, integration, regression, performance, and automated acceptance testing. • Develop CI/CD pipelines, automated deployments, infrastructure automation, and security quality gates. • Implement application monitoring, logging, tracing, alerting, and operational dashboards. • Improve application availability, scalability, reliability, performance, and disaster-recovery readiness. • Lead troubleshooting, root-cause analysis, incident response, and remediation of complex production issues. • Provide technical guidance, coaching, and mentorship to junior and mid-level engineers. • Collaborate with product managers, designers, QA, architects, DevOps, cybersecurity, data teams, and business stakeholders. • Participate in Agile planning, estimation, roadmap development, and delivery activities. • Evaluate emerging technologies based on business value, security, scalability, maintainability, and cost. • Participate in production support activities, including occasional off-hours support. Basic Qualifications and Experience • Bachelor’s or Master’s degree in Engineering, Computer Science, Information Technology, Business, or a related field, with 8–12 years of relevant professional experience. Must-Have Skills • Strong foundation in software architecture, object-oriented design, design patterns, and software-engineering best practices. • Advanced hands-on experience with full-stack software development. • Strong proficiency in Python, TypeScript or JavaScript, and SQL. • Strong proficiency in FastAPI, including API design, validation, asynchronous processing, authentication, testing, and production deployment. • Strong experience developing modern web applications using React and Vite. • Experience with front-end state management, routing, reusable components, responsive design, accessibility, and performance optimization. • Experience designing RESTful APIs, microservices, asynchronous integrations, and event-driven solutions. • Strong cloud-native development experience, with AWS preferred. • Experience with relevant AWS services such as Lambda, ECS, EKS, API Gateway, S3, RDS, DynamoDB, CloudWatch, EventBridge, and Step Functions. • Experience with Docker, Kubernetes, Git, CI/CD, automated testing, and production deployment. • Strong knowledge of secure software development, OWASP Top 10, authentication, authorization, RBAC, encryption, secrets management, and dependency security. • Hands-on experience with application-security and code-quality tools such as Veracode, Snyk, SonarQube, Checkmarx, Fortify, or equivalent platforms. • Experience integrating code, dependency, container, and security scanning into CI/CD pipelines. • Experience assessing and remediating security vulnerabilities and code-quality findings. • Experience designing highly available, scalable, fault-tolerant, and maintainable systems. • Experience with monitoring, logging, tracing, alerting, and production troubleshooting. • Experience leading technical designs, code reviews, and complex software deliveries. • Demonstrated ability to mentor engineers and establish reusable engineering standards. • Strong Agile delivery, analytical, debugging, and problem-solving skills. AI and Machine Learning Capabilities • Experience incorporating AI or machine learning capabilities into enterprise applications. • Understanding of model integration, model serving, APIs, and production deployment patterns. • Familiarity with frameworks such as Scikit-learn, TensorFlow, PyTorch, or equivalent technologies. • Experience developing Generative AI applications using LLMs, prompt engineering, embeddings, vector search, or RAG. • Understanding of AI security, privacy, evaluation, monitoring, governance, and responsible AI. Good-to-Have Skills • Experience with AWS-native serverless and cloud-native architectures. • Experience with Infrastructure as Code using Terraform, AWS CDK, CloudFormation, or equivalent tools. • Experience with observability tools such as CloudWatch, Prometheus, Grafana, Splunk, or OpenTelemetry. • Experience with relational and NoSQL databases and performance optimization. • Experience with Kafka, Amazon Kinesis, Amazon SQS, or other asynchronous and streaming technologies. • Experience with MLOps platforms such as MLflow, SageMaker, Kubeflow, or Airflow. • Experience with Apache Spark, PySpark, Databricks, or other data-processing technologies. • Experience with threat modeling, penetration testing, software composition analysis, and software supply-chain security. • Experience implementing DevSecOps practices across web, API, cloud, and container environments. • Experience with disaster recovery, business continuity, and operational-readiness planning. • Experience within biotechnology, pharmaceutical, life sciences, manufacturing, or another regulated industry. Preferred Certifications • AWS Certified Developer, Solutions Architect, or DevOps Engineer certification. • Relevant cloud, Kubernetes, software architecture, security, or DevSecOps certification. • Relevant AI, machine learning, or Generative AI certification. • Scaled Agile Framework certification. Soft Skills • Excellent analytical, troubleshooting, and decision-making skills. • Strong verbal, written, presentation, and stakeholder-communication skills. • Ability to work effectively with global and virtual teams. • High degree of ownership, initiative, and self-motivation. • Ability to manage multiple priorities, dependencies, and delivery risks. • Strong leadership, mentoring, collaboration, and influencing skills. • Commitment to quality, security, reliability, and operational excellence.