Data Scientist enhancing merchandising and inventory performance using machine learning techniques at Nordstrom. Collaborating with teams to develop data - driven solutions for better customer experiences.
About the role
- Data Scientist developing analytic solutions for CVS Health’s Front Store business using data science to enhance customer satisfaction. Solving problems and optimizing product assortments across various teams.
Responsibilities
- Solve complex problems using operations research, dynamic programming, and reinforcement learning
- Build and improve optimization models to optimize assortment decisions
- Develop and leverage in-depth knowledge of Retail Merchandising business processes
- Translate key drivers of business value to analytics opportunities
- Simulate impact of business decisions to improve customer experience
- Guide the technical approach, leverage large datasets, and build scalable and deployment ready models
- Develop robust methodologies to assess model performance
- Stay up to date on the state-of-the-art modeling methodologies and latest research
- Utilize the latest developments in generative models (LLMs and other AI models) to improve model performance
- Work cross-functionally with a range of technical and non-technical stakeholders including business partners, engineers, and other data and analytics teams
- Share progress, findings, recommendations, and their business implications
- Present meaningful and insights-driven materials on analytical results with recommendations and go forward planning to guide a variety of audiences including internal stakeholders and senior leadership
Requirements
- Bachelor’s degree in a quantitative field such as Operations Research/Industrial Engineering, Applied Mathematics, Computer Science, Engineering, or a related field
- Strong Python and SQL skills, proficiency in working with large datasets
- Experience solving pricing, promotions, assortment, or supply chain problems
- Familiarity with mathematical optimization models using open-source or commercial optimization solvers (such as Pyomo, Gurobi, Pulp, ILOG CPLEX)
- Experience working with a data engineering/MLOps team to deploy data science models
- Familiarity with version control (GitLab or GitHub), and ML platforms (AWS SageMaker, Databricks, GCP Vertex AI, etc.)
- Excellent communication and presentation skills and attention to detail
- Worked in an agile environment, has the flexibility to adapt to changing business needs
- Ability to communicate technical concepts to non-technical audiences, including experience creating communication materials (e.g., white paper, slide decks, etc.)
Benefits
- Affordable medical plan options
- 401(k) plan (including matching company contributions)
- Employee stock purchase plan
- No-cost programs for all colleagues including wellness screenings
- Tobacco cessation and weight management programs
- Confidential counseling and financial coaching
- Paid time off
- Flexible work schedules
- Family leave
- Dependent care resources
- Colleague assistance programs
- Tuition assistance
- Retiree medical access and many other benefits depending on eligibility
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