Data Scientist

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.

The Global Data Insights and Analytics (GDIA) department is looking for qualified individuals who can develop scalable solutions to complex real-world problems using Generative AI, Agentic Workflows, Machine Learning, and Statistics. Our goal is to drive evidence-based decision-making by providing insights from data across various domains, including Connected Vehicle, Smart Mobility, Manufacturing, Supply Chain, and Warranty Analytics.

In this position...

As a Data Scientist, you will play a critical role in leveraging data science to drive significant business impact. You will lead the development of Agentic AI applications and traditional ML models, building intelligent systems that can reason through complex scenarios while also providing predictive and prescriptive insights.

You will be responsible for architecting solutions that are not only intelligent but safe, observable, and robust. You will bridge the gap between modern Large Language Models (LLMs) and traditional statistical techniques, ensuring that AI agents operate within strict guardrails and are backed by rigorous data analysis.

Based in Dearborn, MI, this is a hybrid position with a required four-day onsite presence each week. Relocation assistance may be available for qualified candidates.

The Global Data Insights and Analytics (GDIA) department is looking for qualified individuals who can develop scalable solutions to complex real-world problems using Generative AI, Agentic Workflows, Machine Learning, and Statistics. Our goal is to drive evidence-based decision-making by providing insights from data across various domains, including Connected Vehicle, Smart Mobility, Manufacturing, Supply Chain, and Warranty Analytics.

What you'll do...

* Design and implement supervised and unsupervised machine learning models (e.g., regression, classification, clustering) and statistical experiments to support data-driven decision-making.

* Develop advanced RAG (Retrieval-Augmented Generation) pipelines and API connectors to ingest and synthesize data from diverse sources, including internal databases, unstructured technical documents, and external third-party data.

* Implement robust safety layers and input/output validation using specialized frameworks (e.g., Google Model Armor) to prevent hallucinations, ensure data privacy, and maintain compliance.

* Design and build state-of-the-art AI agents using modern orchestration frameworks (e.g., Lang Graph, Lang Chain, Google ADK) to automate complex reasoning tasks.

* Build comprehensive monitoring pipelines using advanced evaluation tools (e.g., Arize Phoenix, Langfuse) to trace agent reasoning steps, track token usage, and monitor latency in production.

* Adopt rigorous evaluation frameworks (e.g., Ragas, GenAI Evaluation Service) to measure performance. Stay updated on research papers and cutting-edge algorithms in both the GenAI and ML domains.

* Develop and deploy AI solutions exclusively within the Cloud Platform preferable GCP (AWS/Azure) ecosystem, utilizing Vertex AI, Cloud Run, and Big Query.

What you'll do...

* Design and implement supervised and unsupervised machine learning models (e.g., regression, classification, clustering) and statistical experiments to support data-driven decision-making.

* Develop advanced RAG (Retrieval-Augmented Generation) pipelines and API connectors to ingest and synthesize data from diverse sources, including internal databases, unstructured technical documents, and external third-party data.

* Implement robust safety layers and input/output validation using specialized frameworks (e.g., Google Model Armor) to prevent hallucinations, ensure data privacy, and maintain compliance.

* Design and build state-of-the-art AI agents using modern orchestration frameworks (e.g., Lang Graph, Lang Chain, Google ADK) to automate complex reasoning tasks.

* Build comprehensive monitoring pipelines using advanced evaluation tools (e.g., Arize Phoenix, Langfuse) to trace agent reasoning steps, track token usage, and monitor latency in production.

* Adopt rigorous evaluation frameworks (e.g., Ragas, GenAI Evaluation Service) to measure performance. Stay updated on research papers and cutting-edge algorithms in both the GenAI and ML domains.

* Develop and deploy AI solutions exclusively within the Cloud Platform preferable GCP (AWS/Azure) ecosystem, utilizing Vertex AI, Cloud Run, and Big Query.