Data Science Analyst, Distribution Analytics

Join to apply for the Data Science Analyst role at The Home Depot

Join to apply for the Data Science Analyst role at The Home Depot

Position Purpose

The Data Science Analyst will be a pivotal member of our Distribution Analytics team, driving

Req155463

Position Purpose

The Data Science Analyst will be a pivotal member of our Distribution Analytics team, driving strategic decision-making for senior supply chain leaders through advanced data analytics, operations research, and modeling. This role involves applying quantitative methods to optimize hourly associate staffing and various distribution center operations, directly contributing to cost minimization and service maximization. You will leverage your expertise in advanced SQL (with a preference for Google BigQuery), Python programming (with pandas), and operations research techniques (e.g., linear and integer programming) to deliver actionable insights, develop automation solutions, and manage critical data sources. The analyst will regularly support VP+ requests , requiring flexibility to transition seamlessly between urgent ad-hoc tasks and longer-term projects. This is a highly analytical role focused on deep dives and strategic problem-solving, not routine reporting. A strong curiosity to learn and develop a deep understanding of supply chain operations is essential.

Key Responsibilities

• 70% Data Analytics - Collaborate with business stakeholders, data scientists, and business analysts to deliver high quality analytics solutions; Determine best method to gather, model, manipulate and present data; Interpret and translate results from complex analysis into understandable and relevant insights; Perform data analytics for a variety of business problems and opportunities; Apply a wide variety of database applications and analytical tools, including SQL, Google Cloud Big Query and Python; Evaluate, process, analyze and interpret statistical data
• 20% Management of Data - Collaborate with other analysts, data scientists and business partners to explore new sources of data; Cleanse, validate and test data; Standardize and maintain data sources used by the team; Gather, model and manipulate existing data using best practice methodologies
• 10% Technical Learning - Keep up to date on industry trends, best practices and emerging methodologies; Continually develop skills and expertise in data analytics concepts and methodologies; Develop basic data science knowledge through self-learning initiatives and collaboration with team members

Direct Manager / Direct Reports

Travel Requirements

Physical Requirements

Working Conditions

Minimum Qualifications

Preferred Qualifications

Minimum Education

Preferred Education

Minimum Years Of Work Experience

Preferred Years Of Work Experience

Minimum Leadership Experience

Preferred Leadership Experience

Certifications

Competencies

Seniority level

Seniority level

Not Applicable

Employment type

Employment type

Full-time

Job function

Job function

Other

Industries

Consumer Services

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