Job Description

The Global Data Insights and Analytics (GDI&A) department at Ford Motors Company is looking for qualified people who can develop scalable solutions to complex real-world problems using Machine Learning, Big Data, Statistics, Econometrics, and Optimization. The goal of GDI&A is to drive evidence-based decision making by providing insights from data. Applications for GDI&A include, but are not limited to, Connected Vehicle, Smart Mobility, Advanced Operations, Manufacturing, Supply chain, Logistics, and Warranty Analytics.

• Build an in-depth understanding of the business domain and data sources, demonstrating strong business acumen.
• Extract, analyze, and transform data using SQL for insights.
• Apply statistical methods and develop ML models to solve business problems.
• Design and implement analytical solutions, contributing to their deployment, ideally leveraging Cloud environments.
• Work closely and collaboratively with Product Owners, Product Managers, Software Engineers, and Data Engineers within an agile development environment.
• Integrate and operationalize ML models for real-world impact.
• Monitor the performance and impact of deployed models, iterating as needed.
• Present findings and recommendations effectively to both technical and non-technical audiences to inform and drive business decisions.

Qualifications:

• At least 3 years of relevant professional experience applying data science techniques to solve business problems. This includes demonstrated hands-on proficiency with SQL and Python.
• Bachelor's or Master's degree in a quantitative field (e.g., Statistics, Computer Science, Mathematics, Engineering, Economics).
• Hands-on experience in conducting statistical data analysis (EDA, forecasting, clustering, hypothesis testing, etc.) and applying machine learning techniques (Classification/Regression, NLP, time-series analysis, etc.).

Technical Skills:

• Proficiency in SQL, including the ability to write and optimize queries for data extraction and analysis.
• Proficiency in Python for data manipulation (Pandas, NumPy), statistical analysis, and implementing Machine Learning models (Scikit-learn, TensorFlow, PyTorch, etc.).
• Working knowledge in a Cloud environment (GCP, AWS, or Azure) is preferred for developing and deploying models.
• Experience with version control systems, particularly Git.
• Nice to have: Exposure to Generative AI / Large Language Models (LLMs).

Functional Skills:

• Proven ability to understand and formulate business problem statements.
• Ability to translate Business Problem statements into data science problems.
• Strong problem-solving ability, with the capacity to analyze complex issues and develop effective solutions.
• Excellent verbal and written communication skills, with a demonstrated ability to translate complex technical information and results into simple, understandable language for non-technical audiences.
• Strong business engagement skills, including the ability to build relationships, collaborate effectively with stakeholders, and contribute to data-driven decision-making.