Senior Engineer - Data Science

Mission

Core responsibilities

• Define and prioritize AI use cases based on strategic fit, feasibility, value, and scalability.
• Develop machine learning, deep learning, optimization, forecasting, generative AI, and agentic solutions.
• Prepare and validate structured and unstructured data and build reliable, reproducible features.
• Industrialize models through testing, versioning, deployment, monitoring, drift detection, and retraining.
• Apply responsible AI, security, privacy, and governance requirements across the model lifecycle.
• Promote reuse, knowledge sharing, and adoption across international cross-functional teams.

Qualifications and skills

• 3–5 years for an experienced profile or 5+ years for a senior profile delivering data science or AI solutions in production.
• Master’s degree in data science, computer science, applied mathematics, statistics, engineering, or a related quantitative field.
• Strong knowledge of statistics, experimental design, machine learning, forecasting, optimization, and model evaluation.
• Practical experience with deep learning and at least one advanced area such as computer vision, NLP, generative AI, RAG, or AI agents.
• Strong Python and SQL skills and ability to write maintainable production code.
• Experience with data science libraries, APIs, Git, containers, CI/CD, model registries, monitoring, and cloud or enterprise data platforms.
• Knowledge of Agile delivery and strong analytical, storytelling, presentation, and collaboration skills.

Preferred additional experience

• Automotive, manufacturing, engineering, procurement, finance, or product-costing experience.
• Knowledge of cost structures, bills of materials, commodity impacts, purchasing data, budgeting, or profitability analysis.
• Experience with time-series modeling, computer vision, signal processing, optimization, or reinforcement learning.
• Experience with Azure, Databricks, Palantir Foundry, or comparable platforms.
• Knowledge of data governance, explainability, privacy, cybersecurity, and responsible AI practices.
• Experience supporting adoption, change management, or citizen data science communities.

Success measures

About Forvia