Senior Quality Data Scientist at Polaris in Medina, MN

Job description

At Polaris Inc., we have fun doing what we love by driving change and innovation. We empower employees to take on challenging assignments and roles with an elevated level of responsibility in our agile working environment. Our people make us who we are, and we create incredible products and experiences that empower us to THINK OUTSIDE. Position Overview: The Senior Quality Data Scientist develops scalable advanced analytics and artificial intelligence solutions that transform complex data into actionable insights for identifying quality risks, supporting data-driven decisions, and improving product and operational performance. The role works across business and technical functions to translate quality needs into practical, production-ready solutions. You will apply statistical, machine-learning, and AI methods while maintaining appropriate data governance, privacy, security, explainability, human oversight, and documentation standards. This office-based position requires timely analysis, escalation, and decision support in a fast-paced environment shaped by product quality, business risks, regulatory requirements, and executive priorities. Key Responsibilities: Develop datasets, dashboards, metrics, models, and workflows for quality monitoring, risk identification, and performance measurement. Apply statistical process control, reliability and warranty analysis, root-cause methods, predictive modeling, experimentation, and text analytics to identify product, manufacturing, safety, and customer risks. Build, validate, deploy, and monitor analytical and machine-learning solutions that identify underlying causes and emerging trends, provide actionable recommendations, and improve business performance. Develop AI-enabled quality solutions using generative AI, natural language processing, information extraction, anomaly detection, predictive models, and workflow automation. Partner with business and technical stakeholders to prioritize use cases and translate requirements into solutions based on user value, business impact, technical feasibility, and iterative feedback. Communicate findings, assumptions, limitations, and recommended actions to technical and nontechnical stakeholders, and measure solution adoption, performance, operational impact, and realized value. Provide technical guidance, peer review, and knowledge sharing on data science, statistical modeling, and AI practices to strengthen solution quality and analytical capability across the team. Desired Competencies: Critical Thinking: You analyze information objectively, evaluate options, and apply sound judgment to solve problems and make informed decisions. Collaboration: You work effectively with others across functions and levels, contributing to shared goals while respecting different perspectives. Data & Analytical Literacy: You interpret data, metrics, or reporting to inform decisions, identify trends, and measure outcomes relevant to your role. Qualifications: Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, Data Analytics, or a related quantitative field. A minimum of five years of experience in data science, advanced analytics, AI, machine learning, or a related discipline. Experience developing, validating, deploying, and monitoring AI or machine-learning solutions for complex business problems. Proficiency with Python, SQL, statistics, predictive modeling, data preparation, and visualization, with the ability to communicate solutions and findings clearly. Experience applying data science or AI in quality, manufacturing, engineering, service, warranty, safety, customer experience, or another regulated environment preferred. Experience using Snowflake for machine-learning and AI development and deployment, including building user-facing applications with Streamlit, preferred. Ability to work effectively in an office-based environment with frequent interaction across business functions, technical teams, and leadership st