Details:

Stefanini Group is hiring!

Stefanini is looking for a Data Scientist, Dearborn, MI (Onsite)

For quick apply, please reach out Navneet Pathak at 248-213-3677/navneet.pathak@stefanini.com

We are seeking a Data Scientist to develop advanced analytics products that drive vehicle content strategy decisions. This role focuses on applying machine learning, artificial intelligence, statistical modeling, and mathematical optimization to high-impact business problems. The Data Scientist will design, develop, and deploy analytical solutions that support strategic decision-making across North American vehicle programs. This role requires strong quantitative expertise, advanced Python skills, and experience working in cloud-based data environments, particularly Google Cloud Platform (GCP). This role contributes to high-impact analytical engines that influence product and marketing strategy decisions across North American vehicle programs. The position requires a balance of quantitative rigor, practical implementation, and forward-looking application of artificial intelligence.

Responsibilities

Develop and implement machine learning, statistical, and optimization models to support vehicle content strategy.
Write high-quality, production-ready Python code for modeling, experimentation, and data analysis.
Query, manage, and analyze large-scale datasets using GCP tools such as BigQuery.
Partner with Software Engineers to deploy analytics models into production environments aligned with enterprise data architecture and MLOps standards.
Conduct model validation, performance monitoring, and sensitivity analysis to ensure reliability and business relevance.
Translate complex analytical outputs into clear, actionable insights for Marketing and product stakeholders.
Research and apply emerging AI, econometrics, and optimization methodologies to enhance decision systems.

Details:

Required Qualifications

Master's degree or higher in Data Science, Statistics, Economics, Engineering, Mathematics, Operations Research, or a related quantitative field.
2+ years of experience in advanced analytics, including machine learning, mathematical optimization, statistical modeling, econometrics, or AI.
1+ year of experience working with large datasets in cloud-based environments (e.g., GCP).
Strong proficiency in Python for analytical workflows.
Ability to communicate complex analytical concepts to business and product stakeholders.

Preferred Qualifications

PhD in a quantitative discipline.
Experience deploying machine learning or advanced analytics models into production systems.
Familiarity with AI-assisted analytics approaches (e.g., scenario exploration, search space optimization).
Experience in Agile or product-driven environments.
Hands-on experience with Google Cloud Platform.
Strong interpersonal and communication skills with the ability to simplify complex topics for leadership audiences.

**Listed salary ranges may vary based on experience, qualifications, and local market. Also, some positions may include bonuses or other incentives***

Stefanini takes pride in hiring top talent and developing relationships with our future employees. Our talent acquisition teams will never make an offer of employment without having a phone conversation with you. Those face-to-face conversations will involve a description of the job for which you have applied. We also speak with you about the process, including interviews and job offers.

About Stefanini Group

The Stefanini Group is a global provider of offshore, onshore and near shore outsourcing, IT digital consulting, systems integration, application, and strategic staffing services to Fortune 1000 enterprises around the world. Our presence is in countries like the Americas, Europe, Africa, and Asia, and more than four hundred clients across a broad spectrum of markets, including financial services, manufacturing, telecommunications, chemical services, technology, public sector, and utilities. Stefanini is a CMM level 5, IT consulting company with a global presence. We are a CMM Level 5 company.

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