Polaris Inc. is looking to solve complex business decisions for Marketing using data science techniques, including exploratory data analysis and predictive analytics, to drive value for the business and customer.
Requirements
- Strong understanding of statistical methods and predictive/analytical modeling techniques and practices
- Strong experience with one or more data mining/predictive modeling tools: SQL, R, Python, Snowflake
- Proficient with one or more data visualization tools: Tableau, Power BI
- Experience with data preparation, rationalization, and processing in a cloud environment - Azure a plus
- Ability to effectively foster cross-functional relationships across various teams
- Excellent attention to detail and strong organizational skills to manage multiple work requests and projects
- High energy and results oriented
Responsibilities
- Acquire a deep understanding of marketing and business problems facing Polaris and develop end-to-end data driven solutions
- Extract, cleanse, and combine large datasets from multiple sources and systems
- Perform exploratory and targeted analyses, with a wide variety of statistical methods including clustering, regression, decision tree/random forest, time series, neural network, and others
- Collaborate cross-functionally to arrive at actionable insights
- Synthesize results with business input to drive measurable change and effectively communicate technical analyses and results to business management
- Integrate and productionize model results into both cloud and edge compute hardware platforms
- Ensure quality of data & solutions throughout development process
Other
- Bachelor’s degree in Applied Statistics/Mathematics, Data or Computer Science, or work experience equivalent
- 2+ years of professional work experience (post schooling & internships) in a predictive analytics-focused role
- Ability to take on diverse ad-hoc data science requests involving multiple factors that have various scope/goals
- Strong verbal and written communication skills
- Limited travel may be required
