Senior Quality Data Scientist

Polaris Inc.•Medina, MN

1d•$117,000 - $145,000•Onsite

About The Position

The Senior Quality Data Scientist develops scalable advanced analytics and artificial intelligence solutions to 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, applying statistical, machine-learning, and AI methods while maintaining 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 influenced by product quality, business risks, regulatory requirements, and executive priorities. The position also provides technical guidance, peer review, and knowledge sharing to strengthen solution quality and analytical capability across the team. Travel may be required up to 5% depending on business needs and project requirements. The position is not eligible for sponsorship. Former employees must be eligible for rehire, and current employees must be in good standing.

Requirements

Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, Data Analytics, or a related quantitative field.
At least 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, and ability to communicate solutions and findings clearly.
Ability to work effectively in an office-based environment with frequent interaction across business functions, technical teams, and leadership stakeholders.
Ability to travel up to 5% depending on business needs and project requirements.
This position is not eligible for sponsorship.
Former employees must be eligible for rehire; current employees must be in good standing.

Nice To Haves

Experience applying data science or AI in quality, manufacturing, engineering, service, warranty, safety, customer experience, or another regulated environment.
Experience using Snowflake for machine-learning and AI development and deployment, including building user-facing applications with Streamlit.

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 to 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; 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.