Hybrid Data Scientist - Supply Chain Analytics & ML

Polaris Inc.; Plymouth (MN); Hybrid; USD 87,000 - 115,000; Full time

Job summary

Polaris Inc. invites a Data Scientist to optimize supplier risk mitigation within the Supply Chain. You will transform large, varied datasets into actionable insights, build predictive models, and collaborate with cross-functional partners to drive data-driven decisions.

The role focuses on end-to-end analytics, production deployment across cloud/edge platforms, and communicating findings to both technical and non-technical audiences. Minnesota-basedHybrid role with competitive benefits.

Qualifications

• Bachelor’s degree in Applied Statistics, Mathematics, Data Science, Computer Science, or related field.
• Minimum of 2 years of professional experience in a predictive analytics-focused role.
• Demonstrated knowledge of statistical methods and predictive/analytical modeling techniques.
• Experience using data mining and predictive modeling tools such as SQL, R, Python, and Snowflake.
• Experience creating data visualizations using Tableau or Power BI.
• Experience preparing, rationalizing, and processing data in a cloud environment.
• Demonstrated ability to build cross-functional relationships and frame analytical results within a business context.
• Strong organizational skills, attention to detail, and ability to manage multiple projects and priorities.
• Strong verbal and written communication skills, including ability to partner effectively with non-technical stakeholders.
• This position is not eligible for sponsorship.

Responsibilities

• Partner with business stakeholders to understand complex challenges and develop end-to-end data-driven solutions.
• Extract, cleanse, integrate, and prepare large datasets from multiple systems and sources for analysis.
• Perform exploratory and targeted analyses using a variety of statistical methods, including clustering, regression, decision tree/random forest, time series, and neural networks.
• Develop, validate, and optimize predictive and analytical models to generate actionable insights and recommendations.
• Collaborate cross-functionally to translate analytical findings into measurable business improvements.
• Communicate technical analyses, insights, and recommendations effectively to both technical and non-technical audiences.
• Integrate and deploy model results into production across cloud and edge computing platforms.
• Ensure data quality, model performance, and solution integrity throughout the development process.
• Document methodologies, findings, and results using established templates to support knowledge sharing and reuse.
• Gather feedback from business users to continuously improve data science products.

Skills

Communication

Organization

Cross-functional collaboration

Education

Bachelor’s degree (Applied Statistics, Mathematics, Data Science, CS)

Tools

SQL

R

Python

Snowflake

Tableau

Power BI

Job description

Polaris Inc. invites a Data Scientist to optimize supplier risk mitigation within the Supply Chain. You will transform large, varied datasets into actionable insights, build predictive models, and collaborate with cross-functional partners to drive data-driven decisions.

The role focuses on end-to-end analytics, production deployment across cloud/edge platforms, and communicating findings to both technical and non-technical audiences. Minnesota-basedHybrid role with competitive benefits.