Senior Data Scientist - Retail Merchandising
Remote · United States
Job Summary
Senior Data Scientist to lead end-to-end data science initiatives in Retail Merchandising. Design, develop, and deploy AI solutions (ML models, forecasting, optimization) and AI-powered tools (e.g., recommendation systems) for retail and assortment use cases. Work with Corporate AI and BI teams, translate complex business problems into scalable analytical solutions, and mentor junior colleagues. Utilize Databricks (PySpark, MLflow) to deploy production-ready models, build tracking dashboards, and drive data-driven decision making across the DTC Category Management & Merchandising domain. Strong Python, SQL, and analytics skills are essential, with experience in forecasting, NLP, recommendations, and multi-agent or Generative AI approaches favored. Nice-to-have familiarity with Azure, MLOps, and real-time data visualization.
Required Qualifications
- Degree in Data Science, Computer Science, Engineering, Mathematics, or related fields
- Solid experience (typically 4–7+ years) in data science / AI roles with hands-on end-to-end project delivery
- Strong programming skills in Python and experience with Data Science and ML frameworks (pandas, scikit-learn, PyTorch)
- Advanced knowledge in SQL and relational and lakehouse data models
- Proven experience in building and deploying machine learning models in production environments on Databricks (PySpark, MLflow)
- Experience with advanced analytics techniques (e.g., forecasting, optimization, NLP, recommendation systems)
- Strong problem-solving skills and ability to independently drive complex initiatives end-to-end, including mentoring more junior colleagues
- Ability to translate business needs into technical solutions with tangible impact
- Excellent communication skills, with the ability to explain complex concepts to non-technical stakeholders
- Strong collaborator and teamwork member, reference for mentoring more junior colleagues by sharing best practices and knowledge
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