About this role
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.