OVERVIEW:The Director of Athlete Activation Data & Analytics owns enterprise strategies across portfolios, and is responsible for managing people leaders and their teams to deliver value accretive, impactful, strategic analytics & insights that promulgate enterprise strategy. This role sits at the intersection of data, marketing, CRM, and product, and is responsible for turning identity-resolved customer data into actionable insights and measurement frameworks that drive acquisition, onboarding, engagement, loyalty, and long-term value.
As a senior leader, the Director of Analytics demonstrates mastery in the ability to oversee multiple workstreams, projects and initiatives, and forms deep partnership across the business and technology to drive strategic action. The Director of Analytics is a data and analytics evangelist that guides the organization in unbiased data-led insights and measurement strategy to drive business opportunity -- while also informing the underlying foundational data, analytical frameworks, and reporting needs as a translator across stakeholders. A master communicator, the Director of Analytics excels in executive communication.
As a leader of leaders, the Director of Analytics establishes team norms, best practices and processes to drive motivation and engagement across sub teams. As an analytics leader, this role guides analysts and managers, and is responsible for guiding career development for team members and ensuring a strong bench and succession plan across their portfolio. Importantly, the Director of Analytics works in concert with peers to oversee an analytics practice and community across the enterprise.
Job Duties & ResponsibilitiesCustomer Activation & Lifecycle Analytics- Define and operationalize metrics for customer activation across channels (e.g., sign-up, onboarding completion, first purchase/action, early engagement milestones).
- Extend measurement across the full lifecycle, including retention, loyalty, and reactivation.
- Identify friction points in the activation and lifecycle funnels and provide data-driven recommendations to improve conversion and engagement.
CRM & Loyalty Analytics- Partner with CRM and loyalty teams to measure and optimize campaigns across email, SMS, push, and owned channels.
- Evaluate the effectiveness of loyalty programs, rewards structures, and engagement strategies.
- Develop reporting and insights on customer lifetime value (CLV), retention, churn, and loyalty program performance.
- Inform personalization and journey orchestration strategies through data-driven insights.
Customer Segmentation & Propensity Modeling- Lead the development of advanced customer segmentation frameworks based on behavioral, transactional, and demographic data.
- Build and oversee propensity models (e.g., likelihood to convert, churn, upgrade, respond) to drive targeted activation and engagement strategies.
- Enable activation teams with actionable audience segments and model outputs for campaign execution.
- Continuously refine models and segments to improve accuracy, scalability, and business impact.
First-Party Identity Strategy- Partner with data engineering and identity teams to develop a unified customer view using first-party data (CRM, web/app behavior, transactional data, loyalty data, etc.).
- Ensure data quality, consistency, and governance across identity resolution systems.
- Translate identity data into usable segments and signals for activation, personalization, and loyalty initiatives.
Measurement & Reporting- Build scalable dashboards and reporting frameworks to monitor activation, CRM, and loyalty KPIs.
- Establish standardized definitions and methodologies for lifecycle and activation metrics across the organization.
- Deliver clear, actionable insights to executive stakeholders.
- Provides executive summaries of core KPIs and relevant longitudinal trends to unearth 'the why' behind results and patterns
Experimentation & Optimization- Lead A/B and multivariate testing strategies across activation, CRM, and loyalty initiatives.
- Develop incrementality testing approaches to assess true lift from marketing, CRM, and product interventions. Lead communication and application of learnings with Finance and partner teams.
- Drive a culture of test-and-learn within marketing, CRM, and product teams.
Technology & Platform Leadership- Act as key Analytics steward in the implementation, adoption, and optimization of Adobe Customer Journey Analytics (CJA) and Adobe Content Analytics.
- Establish best practices for data modeling, governance, and taxonomy within Adobe CJA and CDP.
- Enable self-service analytics and audience activation through scalable use of Adobe and AI tools.
- Partner with engineering and product teams to enable intelligence at scale through seamless data ingestion, identity stitching, and through development of standardized decision logic and machine consumable knowledge graphs.
Cross-Functional Leadership- Collaborate with Marketing, CRM, Loyalty, Product, Business, and Engineering to align on customer activation and engagement goals.
- Act as a strategic advisor on data-driven decision-making related to customer growth and retention.
- Act as strategic advisor through data led discovery, experimentation, predictive analytics and business case development.
- Communicate complex analytical concepts in a clear and compelling way to non-technical stakeholders.
Team Leadership- Build, mentor, and scale a team of analysts through identification and coaching of strengths, opportunities and how to collaborate to maximize value as a team.
- Foster a culture of curiosity, rigor, and accountability.
- Set priorities and ensure high-quality, timely delivery of insights.
QUALIFICATIONS:Qualifications- 10+ years of experience in analytics, data science, or a related field, with at least 5+ years directly leading teams.
- Bachelor's Degree in Statistics, Computer Science, Business Analytics, Economics, Math, Political Sci, Finance, Engineering, Liberal Arts
- Strong experience working with CRM systems, loyalty programs, and first-party identity data.
- Proven track record of measuring and optimizing customer activation, lifecycle marketing, and retention strategies, inclusive of customer lifetime value.
- Hands-on experience with customer segmentation and propensity modeling techniques.
- Demonstrated success in experimentation design, causal inference, and attribution modeling such as A/B testing, Diff-in-Diff, and synthetic controls.
- Advanced proficiency in SQL and experience with analytics tools (e.g., Python/R, BI platforms like Tableau/Looker).
- Required experience with Adobe Customer Journey Analytics (CJA) and Adobe Customer Data Platform (CDP), including implementation, data modeling, and activation use cases.
- Excellent communication skills with the ability to influence senior stakeholders.
Preferred Qualifications- Experience in a high-growth, data-driven organization (e.g., SaaS, e-commerce, retail, or digital platforms).
- Familiarity with marketing automation and CRM tools (e.g., Salesforce, Braze, Adobe Experience Cloud).
- Familiarity with knowledge graphs and scaling decision loigc
- Experience developing or deploying machine learning models in production environments.
- Experience working with identity graphs, clean rooms, or advanced personalization systems.
VIRTUAL REQUIREMENTS:At DICK'S, we thrive on innovation and authenticity. That said, to protect the integrity and security of our hiring process, we ask that candidates do not use AI tools (like ChatGPT or others) during interviews or assessments.
To ensure a smooth and secure experience, please note the following:
- Cameras must be on during all virtual interviews.
- AI tools are not permitted to be used by the candidateduring any part of the interview process.
- Offers are contingent upon a satisfactory background check which may include ID verification.
If you have any questions or need accommodations, we're here to help. Thanks for helping us keep the process fair and secure for everyone!
Targeted Pay Range: $127,000.00 - $237,800.00. This is part of a competitive total rewards package that could include other components such as: incentive, equity and benefits. Individual pay is determined by a number of factors including experience, location, internal pay equity, and other relevant business considerations. We review all teammate pay regularly to ensure competitive and equitable pay.
