Senior Data Scientist - MET

With a career at The Home Depot, you can be yourself and also be part of something bigger.

Position Purpose:

The Senior Data Scientist is responsible for leading data science initiatives that drive business profitability, process optimization, increased efficiencies, improve workflow automation using AI and improved store associate experience. This role focuses on building industry-leading Agentic AI capabilities and deploying Data Science models at scale for MET operations. Based on the specific data science project, this role would need to be knowledgeable in one or more data science specializations, such as optimization, computer vision, Multimodal AI, Conversational AI, Information Retrieval, Generative AI or search. 

As a Senior Data Scientist, you are expected to seek out business opportunities to leverage data science as a competitive advantage. 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 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. In addition, Data Scientists collaborate with business partners and cross-functional teams, requiring effective communication skills, building relationships and partnerships, and leveraging business acumen 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/or 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 Reports

Travel Requirements:

• Typically requires overnight travel less than 10% of the time.

Physical Requirements:

• Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.

Working Conditions:

• Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

Minimum Qualifications:

• Must be eighteen years of age or older.
• Must be legally permitted to work in the United States.

Preferred Qualifications:

• Masters or PhD in a quantitative field (Computer Science, Math, Statistics, etc.)
• Model Productionization: 4+ years of experience in deploying Data Science models from a development environment to a live application where it serves real-world predictions
• AI Orchestration: 2+ years of experience in Data Science with a focus on Conversational AI, GenAI, Multimodal AI, agentic workflows, custom tool-calling
• Technical Expertise: Must be proficient in a modern scripting language (preferably Python); Must be proficient running queries against data (preferably with Google BigQuery or SQL); proficient utilizing statistical techniques to identify key insights that help solve business problems; knowledgeable in Prescriptive Modeling like optimization, computer vision, recommendation, search or NLP; Demonstrated proficiency in predictive modeling, data mining, and data analysis

Minimum Education:

• The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.

Minimum Years of Work Experience:

• 5

Competencies:

• Attracts Top Talent: Attracting and selecting the best talent to meet current and future business needs
• Business Insight: Applying knowledge of the business and the marketplace to advance the organization's goals
• Collaborates: Building partnerships and working collaboratively with others to meet shared objectives
• Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences
• Cultivates Innovation: Creating new and better ways for the organization to be successful
• Customer Focus: Building strong customer relationships and delivering customer-centric solutions
• Develops Talent: Developing people to meet both their career goals and the organization's goals
• Directs Work: Provides direction, delegating and removing obstacles to get work done
• Drives Results: Consistently achieving results, even under tough circumstances
• Nimble Learning: Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder
• Optimizes Work Processes: Knowing the most efficient and effective processes to get things done, with a focus on continuous improvement
• Self-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels