Data Scientist
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.
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.
3+ years of experience in AI/ML, with proven experience developing and deploying machine learning models in a production environment.
2+ years of experience in GCP with solutions designed and implemented at production scale.
2+ years of experience in advanced modeling, optimization, operational research.
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.