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Associate Data Scientist - Generative BI

homedepot · Store Support Center

New
Mid 🇬🇧 English
Python SQL Google BigQuery Databricks Generative AI GitHub

Job description

About the role

The Home Depot is hiring an Associate Data Scientist - Generative BI to drive business profitability and modernized analytics across the company. The role focuses on practical AI enablement rather than building generative models from scratch: turning user feedback and analytical friction into technical solutions. It sits within the Databricks ecosystem and reports to a manager or above, with no direct reports and no travel required.

Key responsibilities

  • Design and develop algorithms and models against large datasets to create business insights, and support data science projects with effective analysis.
  • Build and maintain rich semantic layers, curate golden SQL query examples, set up automated regression testing pipelines for AI-generated answers, and integrate new enterprise data sources into a scalable multi-agent architecture.
  • Consult with Data Scientists or Senior Data Scientists on the selection, use and interpretation of advanced analytical methods.
  • Learn the assigned business areas so solutions reflect business-specific knowledge.
  • Communicate insights and recommendations to technical and non-technical audiences, and support reports, updates and presentations.
  • Keep up to date on industry trends and best practices, and apply what is learned.

Required profile

  • Age 18 or older and legally permitted to work in the United States.
  • Preferred: Master's degree in a quantitative field (Computer Science, Math, Statistics, etc.) or equivalent experience.
  • Preferred: 3+ years of experience in business intelligence and analytics.
  • Preferred: experience with generative AI chatbots, LLMs or conversational analytics, and with the Databricks ecosystem.

Required skills

  • Preferred: modern scripting language (preferably Python).
  • Preferred: querying data, preferably with Google BigQuery or SQL.
  • Preferred: statistical techniques, predictive modeling, data mining and data analysis.
  • Preferred: GitHub repositories and standard CI/CD practices.

Questions fréquentes

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Source : ats:workday

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Published 5 hours ago

Expires 1 month from now

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