Senior Director, Data Science - Marketing

About the role

The Home Depot is looking for a Senior Director, Data Science to define and execute the data science vision for its Core Marketing and Retail Media organizations. The role partners with Marketing, Retail Media, Customer Analytics, Product, Technology, Finance and other business stakeholders to drive growth in customer acquisition, engagement, personalization, media effectiveness and revenue through advanced analytics, machine learning and AI. It leads a team of data scientists and sets the long-term data science roadmap, reporting to a Vice President or above with five direct reports.

Key responsibilities

• Data Science Advocacy (40%): align with business leaders, act as escalation point, champion data science capabilities and define metrics against business goals.
• People Management and Team Leadership (20%): mentor and coach direct reports, attract and develop talent, build onboarding and training plans, foster collaboration and celebrate results.
• Strategy and Business Development (40%): seek new business opportunities, shape the operating model and cost structure of Data Science, build trust with internal customers, support research and innovation, and drive adoption of predictive and prescriptive techniques.

Required profile

• At least 18 years old and legally permitted to work in the United States.
• 12+ years leading advanced analytics, data science, machine learning or AI teams in large consumer, retail, eCommerce, digital marketing or media organizations.
• 7+ years of people leadership experience building and leading data science teams.
• Deep expertise in marketing analytics, customer behavior modeling, personalization, CLV, segmentation, forecasting and predictive modeling.
• Experience with Retail Media Networks, digital advertising, ad-tech, media measurement, attribution and incrementality testing.
• Proven track record of influencing executive stakeholders and establishing measurement frameworks and governance standards.

Required skills

• Cloud platforms such as Snowflake, Databricks, Azure, Google Cloud Platform and AWS.
• Python, R, SQL and machine learning frameworks.
• A/B testing, causal inference, marketing mix modeling, multi-touch attribution and experimentation.