Senior Data Scientist - AI, Agentic Analytics & RAG

Ford; Dearborn (MI); Hybrid; USD 85,000 - 193,000; Full time

Benefits offered by this job

Medical, dental, vision

Prescription drug coverage

Family care days

Parental leave

Back-up child care

Tuition assistance

Employee resource groups

Paid time off

Paid holidays

Job summary

Ford's Global Data Insight & Analytics (GDIA) team seeks a Data Scientist to own the analytic lifecycle from problem definition to deployment. You will work with Product Managers, Designers, Software Engineers and fellow Data Scientists to deliver impactful insights using modern statistics, ML, and generative AI techniques.

The role emphasizes agent orchestration, contextual retrieval, and efficient AI design with a hybrid onsite requirement and collaboration across enterprise analytics domains.

Qualifications

• Master's degree in a relevant field.
• 5+ years of experience in statistical or mathematical modeling, ML, Data Science or AI engineering.
• 3+ years of cloud platform experience (GCP, Azure, AWS).
• 1+ years designing, developing, deploying Agentic AI solutions incl. RAG pipelines and LLM/SLM integrations.
• 1+ years of experience in Accounting or Finance.
• Strong communication and problem solving skills.

Responsibilities

• Translate business problems into analytic solutions and models.
• Develop and validate analytic models and assess performance.
• Design multi-step reasoning frameworks and agentic loops.
• Ensure data quality and communicate insights to technical and non-technical audiences.
• Collaborate with Product Managers, Designers and Engineers to deliver analytic solutions.

Skills

Statistics

Machine Learning

Data Science

AI Engineering

Problem solving

Communication

Education

Master's degree in Statistics, Economics, Data Science, Computer Science, Engineering, Mathematics

Tools

LangChain

LlamaIndex

Haystack

GCP/AWS/Azure

LLM/SLM APIs

RAG pipelines

Job description

Ford's Global Data Insight & Analytics (GDIA) team seeks a Data Scientist to own the analytic lifecycle from problem definition to deployment. You will work with Product Managers, Designers, Software Engineers and fellow Data Scientists to deliver impactful insights using modern statistics, ML, and generative AI techniques.

The role emphasizes agent orchestration, contextual retrieval, and efficient AI design with a hybrid onsite requirement and collaboration across enterprise analytics domains.