Data Scientist

We made history and now we work to transform the future – for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters.

Do you believe data tells the real story? We do! Redefining mobility requires quality data, metrics and analytics, as well as insightful interpreters and analysts. That's where Global Data Insight & Analytics makes an impact. We advise leadership on business conditions, customer needs and the competitive landscape. With our support, key decision makers can act in meaningful, positive ways. Join us and use your data expertise and analytical skills to drive evidence-based, timely decision making.

In this position...

We are seeking a Data Scientist for the EV Core Experience team within the Global Data Insights & Analytics (GDIA) organization's Strategy & Enterprise Analytics (SEA) team. Our team develops innovative, cloud-native AI and analytics solutions that optimize the electric vehicle lifecycle and enhance core engineering processes. We focus on delivering high-impact data products that leverage vehicle telematics, advanced machine learning, and generative AI to solve complex challenges across EV performance, energy management, and engineering design automation.

As a Data Scientist, you will be a key player in bridging the gap between complex data streams, engineering requirements, and actionable AI solutions that drive Ford’s EV leadership

Based in Allen Park, MI, this is a hybrid position with a required four-day onsite presence each week 

 

What you'll do...

• Acquire a deep understanding of complex engineering and business problems and translate them into scalable AI/ML solutions.
• Design, develop, and implement end-to-end AI/ML pipelines, from data ingestion and preprocessing to model training, evaluation, and deployment.
• Ingest, transform, and analyze large datasets to support the team in launching data products in the Data Factory on Google Cloud Platform (GCP). 
• Act as a full-stack data scientist to develop and deliver advanced analytics models, including forecasting, anomaly detection, optimization, LLM, and more.
• Write clean, efficient, and well-documented code in Python for data manipulation, feature engineering, and production-level model development.
• Collaborate internally and externally to identify new and novel data sources and explore their potential use in developing actionable business results
• Examine, interpret and report analytical results in both written reports and in oral presentations to varied audiences

You'll have...

• Master's degree (M.S.) in Data Science, Computer Science, Industrial & System Engineering, Mechanical Engineering, or a related quantitative field or equivalent combination of relevant education and experience.
• 2+ years of experience in AI/ML, with proven experience developing and deploying machine learning models in a production environment. Equivalent experience gained through internships or specialized coursework may be acceptable
• 2+ years of experience in cloud, GCP preferred, with solutions designed and implemented at production scale. Equivalent experience gained through internships or specialized coursework may be acceptable.
• 2+ years of experience in advanced modeling, optimization, operational research Equivalent experience gained through internships or specialized coursework may be acceptable.

Even better, you may have...

• Ph.D. in Data Science, Computer Science, Business Analytics, Machine Learning, Statistics, or a related quantitative field.
• Expertise in SQL for data querying, manipulation, and database interaction.
• Solid understanding of machine learning algorithms, statistical modeling, and data analysis techniques.
• Excellent oral, written, and interpersonal communication skills.
• Experience working with Terraform to provision Infrastructure as Code.
• Experience in the electrification and/or transportation domain, specifically regarding battery chemistry or vehicle powertrain systems.
• Experience in forecasting algorithms, anomaly detection algorithms, multi-objective optimizations, or physics-informed neural networks. 
• Experience in Generative AI, includi