Senior, Data Scientist - Merchandising Analytics (member and Insights)

Walmart Walmart · Retail · Bentonville, AR

Senior Data Scientist role focused on merchandising analytics, leveraging data and AI to drive assortment, pricing, and inventory decisions. The role involves analyzing complex datasets, building and deploying data products and models, designing algorithms and AI/ML models, applying Causal Inference and Generative AI, and communicating insights. Requires strong data science, machine learning, and Python/PySpark skills, with experience in data engineering and causal frameworks.

What you'd actually do

  1. Analyze complex datasets to uncover trends, patterns, and opportunities.
  2. Translate complex business challenges into analytical solutions.
  3. Build and deploy scalable data products and models.
  4. Design and develop state-of-the-art algorithms, AI/ML models, and optimization techniques to generate actionable business insights.
  5. Apply Causal Inference techniques to traverse the data and pinpoint the true root cause (RCA).

Skills

Required

  • 5+ years of hands-on professional work experience as a data scientist
  • Proven track record and demonstrated experience translating complex business needs into data-driven solutions that deliver measurable impact and align with strategic objectives.
  • Strong knowledge of data engineering, including data pipelines, data quality, and database technologies such as SQL and NoSQL.
  • Extensive experience in data science, machine learning, and predictive modeling with proficiency in Python and PySpark programming.
  • Strong understanding of causal frameworks, forecasting methodologies and anomaly detection techniques
  • Proficiency in data visualization tools (Power BI) and techniques to effectively communicate insights to stakeholders.
  • Ability to communicate complex ideas clearly to technical and non-technical audiences.
  • Ability to perform well under pressure, maintain focus, and deliver high-quality outcomes in a fast-paced, ambiguous, and dynamic environment.

Nice to have

  • Professional work experience with Spark and Dashboards.
  • Working knowledge and understanding of GenAI and AI solutions.

What the JD emphasized

  • deliver scalable, data-driven solutions
  • generate actionable business insights
  • deliver measurable impact
  • deliver high-quality outcomes

Other signals

  • apply foundational machine learning techniques
  • working understanding of Generative AI
  • build the algorithmic logic that evaluates the root cause and recommends the optimal intervention