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Sr Data Scientist, Pricing Analytics; Deep Learning

Job in Atlanta, Fulton County, Georgia, 30383, USA
Listing for: The Home Depot
Full Time position
Listed on 2025-12-21
Job specializations:
  • IT/Tech
    Data Analyst, Data Scientist, AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 90000 USD Yearly USD 90000.00 YEAR
Job Description & How to Apply Below
Position: Sr Data Scientist, Pricing Analytics (Deep Learning)

Sr Data Scientist, Pricing Analytics (Deep Learning)

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This range is provided by The Home Depot. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$90,000.00/yr - $/yr

Req
162601

The Home Depot is able to offer virtual employment of this position in the following states: AK, AZ, CA, GA, HI, , IL, KS, KY, ME, MA, MI, MN, MT, NE, NV, NH, NJ, NM, NY, ND, OH, OR, RI, SD, TX, UT, VT, WA, WV, WI, WY

Position Purpose

The Sr. Data Scientist is responsible for leading data science initiatives that drive business profitability, increased efficiencies and improved customer experience. This role assists in the development of the Home Depot advanced analytics infrastructure that informs decision making. Sr. Data Scientists are expected to seek out business opportunities to leverage data science as a competitive advantage. This team works with forecasting possible outcomes of price and promotion actions at different levels, including AI solutions, and would need to be Proficient in deep learning and forecasting techniques.

As a Sr. Data Scientist, you will serve as a lead on data science projects, collaborating with project/product managers, providing prioritization of tasks, balancing workload and mentoring data scientists on the project team. This role is expected to present insights and recommendations to leaders and business partners and explain the benefits and impacts of the recommended solutions. This role supports the building of skilled and talented data science teams by providing input to staffing needs and participating in the recruiting and hiring process.

In addition, Data Scientists collaborate with business partners and cross-functional teams, requiring effective communication skills, building relationships and partnerships, and leveraging business proficiency to solutions and recommendations.

Key Responsibilities
  • 35% Solution Development – Proficiently design and develop algorithms and models to use against large datasets to create business insights;
    Execute tasks with high levels of efficiency and quality;
    Make appropriate selection, utilization and interpretation of advanced analytical methodologies;
    Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners;
    Prepare reports, updates and presentations related to progress made on a project or solution;
    Clearly communicate impacts of recommendations to drive alignment and appropriate implementation.
  • 30% Project Management & Team Support – Work with project teams and business partners to determine project goals;
    Provide direction on prioritization of work and ensure quality of work;
    Provide mentoring and coaching to more junior roles to support their technical competencies;
    Collaborate with managers and team in the distribution of workload and resources;
    Support recruiting and hiring efforts for the team.
  • 20% Business Collaboration – Leverage extensive business knowledge into solution approach;
    Effectively develop trust and collaboration with internal customers and cross-functional teams;
    Provide general education on advanced analytics to technical and non-technical business partners;
    Deep understanding of IT needs for the team to be successful in tackling business problems;
    Actively seek out new business opportunities to leverage data science as a competitive advantage.
  • 15% Technical Exploration & Development – Seek further knowledge on key developments within data science, technical skill sets, and additional data sources;
    Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects;
    Define best practices and develop clear vision for data analysis and model productionalization;
    Contribute to library of reusable algorithms for future use, ensuring developed codes are documented.
Direct Manager/Direct Reports
  • This position reports to manager or above.
  • This position has 0 Direct…
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