Senior Director, Data Science - Marketing

Home Depot • Atlanta, GA

2d • Onsite

About The Position

The Sr. Director, Data Science is a strategic leader responsible for defining and executing the data science vision that powers The Home Depot’s Core Marketing and Retail Media organizations. This role partners closely with Marketing, Retail Media+, Customer Analytics, Product, Technology, Finance, and Business stakeholders to drive measurable growth in customer acquisition, engagement, personalization, media effectiveness, and revenue generation through advanced analytics, machine learning, and AI-driven solutions. The Sr. Director will lead a high-performing team of data scientists responsible for developing predictive models, customer segmentation strategies, marketing measurement frameworks, attribution methodologies, experimentation programs, and media optimization solutions. This leader will translate complex business challenges into scalable analytical strategies that improve marketing performance, customer experience, and return on advertising spend. As a Sr. Director, this role establishes the long-term data science roadmap for Marketing and Retail Media, influences executive decision-making through data-driven insights, and collaborates across the organization to ensure alignment with enterprise goals. The Sr. Director is accountable for delivering significant business impact through analytics innovation, talent development, operational excellence, and disciplined investment prioritization. This role also oversees governance, measurement standards, and value realization frameworks to ensure data science initiatives deliver measurable business outcomes and return on investment.

Requirements

• Must be at least 18 years old
• Must be legally permitted to work in the United States
• Master's degree or Ph.D. in Data Science, Statistics, Mathematics, Computer Science, Economics, Operations Research, or a related quantitative field.
• 12+ years of experience leading advanced analytics, data science, machine learning, or AI teams within large-scale consumer, retail, eCommerce, digital marketing, or media organizations.
• 7+ years of people leadership experience, including building, developing, and leading high-performing teams of data scientists, analytics managers, and technical leaders.
• Deep expertise in marketing analytics, customer behavior modeling, personalization, customer lifetime value (CLV), segmentation, forecasting, and predictive modeling.
• Extensive experience supporting Retail Media Networks (RMNs), digital advertising, ad-tech, mar-tech, media measurement, attribution, incrementality testing, and advertising optimization.
• Demonstrated success leveraging machine learning, AI, and advanced analytics to drive measurable business outcomes, customer growth, media effectiveness, and revenue.
• Expertise in experimentation methodologies, including A/B testing, causal inference, marketing mix modeling (MMM), multi-touch attribution (MTA), and incrementality measurement.
• Strong knowledge of cloud-based analytics ecosystems, including Snowflake, Databricks, Azure, Google Cloud Platform, AWS, and modern data science toolsets.
• Advanced proficiency with Python, R, SQL, and machine learning frameworks.
• Experience leading large-scale analytics transformations and influencing executive stakeholders across Marketing, Product, Technology, Finance, and Operations.
• Proven ability to translate complex analytical concepts into clear, actionable business strategies for executive audiences.
• Strong business acumen with the ability to align data science investments to commercial outcomes, customer value, and enterprise growth objectives.
• Successful track record establishing measurement frameworks, governance standards, operating models, and talent strategies within highly matrixed organizations.
• Exceptional executive communication, storytelling, stakeholder management, and change leadership skills.
• Demonstrated ability to build strategic partnerships and influence decisions at the VP and Executive Leadership Team level.
• 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.
• 10+ years of experience
• 5 years of leadership experience

Nice To Haves

• The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.

Responsibilities

• Collaborate with business leaders and executive level leaders to align on objectives and expectations
• Serve as escalation point for any issues or difficulties with specific projects or initiatives
• Champion data science capabilities and new skills to continually identify ways to impact the business
• Define effective metrics to understand the high-level performance against business goals
• Provide leadership, mentorship and coaching to direct reports and evaluate performance, execution, and contribution
• Establish a clear vision for the team and influence reach with business partners
• Attract, retain and develop top talent to build an effective and high performing teams
• Support team in development of business knowledge and technical skills with clear plans and regular assessment of progress
• Develop onboarding and training plan for both technical and soft skills that will ensure high level of capabilities within the team
• Foster collaboration and alignment between different data science roles to develop a supportive and engaged team
• Ensure best practices and world-class techniques are leveraged in the solutioning for business problems and future team reach
• Drive team's results and celebrates accomplishments
• Leverage extensive business knowledge and relationships to seek out new business opportunities to leverage data science and advocate for team's skills
• Ensure a successful operating model and cost structure for Data Science is developed and leveraged across the enterprise to standardize ROI calculations and project/team funding
• Effectively develop trust and collaboration with internal customers and cross-functional teams
• Support data science research and innovation efforts that can serve as competitive advantage for the enterprise
• Develop an integrated data science vision and end-to-end strategy
• Drive adoption of leading-edge data science techniques and methods, both predictive and prescriptive

What This Job Offers

• Job Type: Full-time
• Career Level: Senior