Jobs at Tata Consultancy Services

Role - Azure Data Factory Developer/ Lead Experience - 6 to 12 years Joining Location - PAN INDIA Interview location - Bengaluru , 13 Jun Saturday Job descriptio n Technical/Functional Skil ls•Azure Data Factory: In-depth knowledge of ADF, including data integration, ETL development, and pipeline orchestratio n.•Azure Synapse Analytics: Strong understanding of Azure Synapse Analytics, including data warehousing, data modeling, and data queryin g.•Azure Data Services: Familiarity with Azure data services, including Azure Databricks, Azure Cosmos DB, and Azure Blob Storag e.•Expertise in Azure Stream Analytics & Event Hu bs•Programming: Proficiency in programming languages, including Python, PowerShell, or SQ L.•Communication: Excellent communication and collaboration skill s.•Azure Certifications: Relevant certifications, such as Azure Data Engineer Associate or Azure Data Scientist Associat e.•Cloud Experience: Experience with cloud-based data platforms, including AWS or Google Clou d.•Big Data: Experience with big data technologies, including Hadoop, Spark, or NoSQL database s.•Data Science: Experience with data science tools, including Python, R,

Role - Data Scientist Experience - 4 to 15 years • Advanced degree in mathematics, statistics, computer science, or related field • .Strong knowledge of statistical analysis, machine learning, and deep learning • .Developing advanced algorithms and models to extract valuable insights from complex datasets, with a focus on generative AI and large language models (LLMs) • .Conducting thorough exploratory data analysis (EDA) to uncover patterns, anomalies, and correlations in the data for NLP/Time series/Vision capability streams • .Fine-tuning pre-trained models to optimize their performance for specific tasks and domains • .Strong working knowledge of agent-based and Agentic AI systems leveraging LLMs for reasoning, planning, and task execution • .Collaborating with cross-functional teams to define project objectives and deliverables and integrating AI models into production environments • .Applying statistical techniques, machine learning algorithms, and deep learning architectures to solve complex business problems and generate accurate predictions • .Utilizing cloud-based AI services (e.g., AWS, Azure, GCP) to build scalable and efficient AI solutions • .Implementing MLOps practices for model deployment, monitoring, and management • .Proficiency in Python or R, along with relevant libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow, PyTorch) • .Staying updated with the latest advancements in data science, generative AI, and cloud AI services • .Experience in developing and deploying AI/Gen AI based systems in production • .Mentoring junior data scientists and providing technical guidance .