Senior Data Scientist (remote)

About the position If you are local to Milwaukee we require at minimum 3 days in office What you will do In this exciting role you will lead the effort to build and maintain a digital twin of our mission critical North American closed-loop critical minerals supply chain. This is not only a $2.2B global network that represents over half of Clarios’ NA’s cost of goods sold, it also is a vital for the US economy – directly enabling consumers and business to stay on the road! This will require working with predictive, prescriptive analytics and decision-intelligence across the US / Canada region at Clarios. You’ll apply modern statistics, machine learning and AI to real manufacturing and supply chain problems, working side-by-side with our business stakeholders and our global analytics team to deploy transformative solutions- not just models. How you will do it Build production-ready ML/statistical models (regression/classification, clustering, time series, linear / non-linear optimizations) to detect patterns, perform scenario and what if analytics and generate prescriptive insights / outcomes. Wrangle and analyze and model data with Python and SQL; perform feature engineering, data quality checks, and exploration analysis to validate hypotheses and model readiness. Develop digital solutions /visuals in Power BI and our decision intelligence platform to communicate results and monitor performance with business users. Partner with stakeholders to clarify use cases, translate needs into technical tasks/user stories, and iterate solutions in sprints. Manage model deployment (e.g., packaging models, basic MLOps) with guidance from Global Analytics Lead complex solution development, scoping and utilize design thinking principles for customer centric model delivery Document and communicate model methodology, assumptions, and results to non-technical audiences; support troubleshooting and continuous improvement of delivered analytics. Deliver value realization as part of our business analytics team to drive positive business outcomes for our metals team. Potential travel up to 5-10%

Responsibilities

• Build production-ready ML/statistical models (regression/classification, clustering, time series, linear / non-linear optimizations) to detect patterns, perform scenario and what if analytics and generate prescriptive insights / outcomes.
• Wrangle and analyze and model data with Python and SQL; perform feature engineering, data quality checks, and exploration analysis to validate hypotheses and model readiness.
• Develop digital solutions /visuals in Power BI and our decision intelligence platform to communicate results and monitor performance with business users.
• Partner with stakeholders to clarify use cases, translate needs into technical tasks/user stories, and iterate solutions in sprints.
• Manage model deployment (e.g., packaging models, basic MLOps) with guidance from Global Analytics Lead complex solution development, scoping and utilize design thinking principles for customer centric model delivery
• Document and communicate model methodology, assumptions, and results to non-technical audiences; support troubleshooting and continuous improvement of delivered analytics.
• Deliver value realization as part of our business analytics team to drive positive business outcomes for our metals team.

Requirements

• Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, or related field—or equivalent practical experience.
• 3-5 years of applying ML/statistics on business data.
• Python proficiency (pandas, scikit-learn, SciPy/statsmodels) and SQL across common platforms (e.g., SQL Server, Snowflake).
• Core math/stats fundamentals: probability, hypothesis testing/DoE basics, linear algebra, and the principles behind common ML methods.
• Data visualization experience with Power BI / Decision Intelligence Platforms for analysis and stakeholder storytelling.
• Ability to work in cross-functional teams and explain technical work clearly to non-technical partners.
• Candidates must be self-driven, curious, and creative

Nice-to-haves

• Cloud & big data exposure: Azure (or AWS), Databricks/Spark; Snowpark is a plus.
• Understanding of ETL/ELT tools such as ADF, SSIS, Talend, Informatica, or Matillion.
• MLOps concepts (model validation, monitoring, packaging with Docker/Kubernetes).
• Deep learning basics (PyTorch/Keras) for the right use cases.
• Experience contributing to agile backlogs, user stories, and sprint delivery.
• 5+ years of experience in data analytics
• Master’s Degree in Statistics, Economics, Data Science or Computer Science.

Benefits

• Medical, dental and vision care coverage and a 401(k) savings plan with company matching – all starting on date of hire
• Tuition reimbursement, perks, and discounts
• Parental and caregiver leave programs
• All the usual benefits such as paid time off, flexible spending, short-and long-term disability, basic life insurance, business travel insurance, Employee Assistance Program, and domestic partner benefits
• Global market strength and worldwide market share leadership
• HQ location earns LEED certification for sustainability plus a full-service cafeteria and workout facility

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