Senior Data Scientist - AI, Pricing & Competitive Insights

Homedepot

United States

Remote

USD 90,000 - 190,000

Full time

14 days+
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Benefits offered by this job

Health care benefits
401K
ESPP
Paid time off
Success sharing bonus

Job summary

The Home Depot is seeking a Senior Data Scientist to help build a data-driven center of excellence for competitive intelligence and pricing. You will design algorithms, scale data analyses, and deploy ML solutions that influence pricing, assortment, and BI decisions for a Fortune 25 company.

The role requires advanced analytics skills, strong Python/SQL, and collaboration with cross-functional teams. Travel is limited and the environment is fast-paced and data-driven.

Qualifications

  • Bachelor's degree in a quantitative field; 7+ years work experience.
  • 7+ years of data science experience with data analysis, ML, and pricing/AI.
  • Strong Python and SQL; experience with data cleaning, predictive analytics, and causal inference.

Responsibilities

  • Design and develop algorithms and models for large datasets to generate insights.
  • Guide prioritization, quality, and development of direct reports.
  • Create scalable processes for large-scale data analyses and model deployment.
  • Use data-driven insights to optimize price points.
  • Stay current with advances in data science and ML.

Skills

Python
SQL
Data cleaning
Predictive analytics
Machine learning
Generative AI
AI system design
Cloud AI platforms

Education

Bachelor's degree in a quantitative field

Tools

Cloud AI platforms
Multimodal models

Job description

The Home Depot is seeking a Senior Data Scientist to help build a data-driven center of excellence for competitive intelligence and pricing. You will design algorithms, scale data analyses, and deploy ML solutions that influence pricing, assortment, and BI decisions for a Fortune 25 company.

The role requires advanced analytics skills, strong Python/SQL, and collaboration with cross-functional teams. Travel is limited and the environment is fast-paced and data-driven.

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