Senior Data Scientist, Go-to-Market Analytics & Pricing

Ford; Dearborn (MI); Presencial; USD 120.000 - 190.000; Jornada completa

Descripción de la vacante

Ford Motor Company is seeking a yield optimization analytics expert to advance pricing and incentive strategy across the business. You will own end-to-end lifecycle of predictive models and production-ready analytics, delivering insights via web apps or dashboards.

You'll collaborate with data engineering and AI/ML teams, apply ML, econometrics, and optimization to real business constraints, and explore agentic AI and LLM-based tooling to enhance modeling workflows.

Formación

• Master's degree required or equivalent in a quantitative field.
• 3+ years of data analytics, AI/ML modeling, or related quantitative analysis.
• Proficiency in programming languages (Python, R, MATLAB, C/C++/C#, SAS) and SQL.

Responsabilidades

• Own end-to-end lifecycle of complex predictive models and optimization frameworks.
• Ensure data accuracy, calculation logic, and business assumptions.
• Drive deployment automation and maintain production-ready assets.
• Explore agentic AI or LLM-based tools to improve modeling workflows.
• Partner with business stakeholders to translate needs into analytical problems.
• Communicate quantitative concepts to technical peers and business partners.
• Execute rapid ad-hoc analytical requests to support decisions.

Conocimientos

Python

R

SQL

Machine Learning

Statistics

Optimization

Educación

Master's degree in Data Science/Statistics/Economics/OR related

Ph.D. in Data Science/Statistics/Economics/OR related

Herramientas

Dash

Flask

Streamlit

Git

Azure

GCP

Descripción del empleo

Ford Motor Company is seeking a yield optimization analytics expert to advance pricing and incentive strategy across the business. You will own end-to-end lifecycle of predictive models and production-ready analytics, delivering insights via web apps or dashboards.

You'll collaborate with data engineering and AI/ML teams, apply ML, econometrics, and optimization to real business constraints, and explore agentic AI and LLM-based tooling to enhance modeling workflows.