Senior Data Scientist, Delivery

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

Position Purpose:

We are looking for a Senior Data Scientist to support innovation and next-gen Delivery experience solutions for Home Depot. If you are tech-savvy, deeply passionate about Data-driven solutions, AI/ML tools and platforms as well as curious about understanding the complex processes behind important business decisions - please apply. The more specific technical requirements are mentioned below:

ML Depth - Solid hands-on experience with tree-based ranking and classification models (XGBoost, etc.) is table stakes, but practitioner-level depth with NLP, BERT-family embedding models, similarity search, DNNs or building multi-modal models will have an edge and be needed in the work. Expertise with these advanced models not needed, will get chance and time to learn on the job - but a headstart will help.

Deployment Mindset - You have taken models beyond notebooks - pipelines, non-prod deployments, and experience on Vertex AI pipelines and custom jobs.

Experimentation familiarity - You are not new to designing and reading an A/B test or other methods for measurement.

Familiarity with LLM/Agentic workflows - Recent hands-on experience with LLM pipelines, RAG, or working with LLMs programmatically in the last 12 months. Experience with Agentic workflows will stand-out during the interview process.

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:

• PhD in a quantitative field (Computer Science, Math, Statistics, etc.)
• 6+ years of experience in business intelligence and analytics
• Working knowledge of Microsoft Excel and Power Point
• Proficient in a modern scripting language (preferably Python)
• Proficient running queries against data (preferably with Google BigQuery or SQL)
• Proficient with data visualization software (preferably Tableau)
• Mastery utilizing statistical techniques to identify key insights that help solve business problems
• Proficient 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.

Preferred Education:

• No additional education

Minimum Years of Work Experience:

• 5

Preferred Years of Work Experience:

• No additional years of experience

Minimum Leadership Experience:

• None

Preferred Leadership Experience:

• None

Certifications:

• None

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