Jobs at Ford Motor Private Limited

• Data Collection & Management: Acquire data from primary or secondary data sources and maintain databases/data systems. Fully understand the data sources and quality to ensure it’s usage for meaningful inference. • Data Cleaning, transformation and automation: Filter and “clean” data to ensure “data input” for processing will lead to meaningful inference. Build automated systems to quickly transform data into information for management. • Analysis & Interpretation: Interpret data, analyze results using appropriate dimensions and even statistical techniques (where required). Identify, analyze, and interpret trends or patterns in complex data sets. Perform Variance analysis • Visualization & Reporting: Develop and implement data analyses, data collection systems, and other strategies that optimize efficiency and quality. Create dashboards and visualizations to communicate findings to stakeholders. • Collaboration: Coordinate with IT, GDIA, and business teams to ensure data integrity and to understand the context of the data being analysed. • Data Automation: Replace manual, Excel-heavy processes for actuals and forecast with automated ETL pipelines and dashboards. Ensure 'one version of the truth' across all financial reports. • Ad-hoc Analysis: Support Skill Team Controllers with rapid-response data / scenario analysis. MP&L Finance • Data Collection & Management • Data Cleaning, transformation and automation • Analysis & Interpretation • Visualization & Reporting • Process Improvement • Collaboration • Data Automation • Support Financial submission • Support Skill Team Controllers with rapid-response data / scenario analysis • Technical Qualification: • Data Tools: Proficiency in SQL for database / Data Forms querying is essential. • Programming: Experience with programming languages used for analysis, such as Python or R. • Finance Knowledge: Knowledge of Order of Variance analysis. • Cloud Computing: Proficiency in deploying models on cloud platforms such as Google Cloud (Vertex AI), Cloud integration (Azure/AWS/GCP), Data Lakes, and Enterprise Data Platforms (EDP). • Visualization: Expertise in data visualization tools like Power BI. • Spreadsheets: Advanced knowledge of Microsoft Excel, Power Pivot, Power Query, and VBA. • Mathematics & Statistics: Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy. Qualification: MBA Finance with bachelor’s degree in computer science, Electrical Engineering, or a related field 2+ years’ experience in a data analytics role including running queries, compiling data, and transformation data from separate sources to form unified sets for analysis. 2+ years’ experience in at least one of the following languages: Python, R, SQL, or similar languages.