Manager of Analytics

Key Responsibilities

• Lead end-to-end analytical workstreams across Retail, Brand, Innovation and Affiliate channels
• Partner with business stakeholders to frame hypotheses, define analytical approaches, and ensure analyses are grounded in clear business questions
• Identify core performance drivers and synthesize insights that explain what happened, why it happened, and what to do next
• Apply advanced analytical techniques to evaluate campaigns, promotions, launches, and ongoing channel performance
• Own the development, iteration, and maintenance of advanced analytical models and experimentation frameworks for assigned channels
• Develop and apply marketing measurement frameworks, including attribution and media mix modeling
• Design and interpret experiments and quasi-experiments to assess incrementality and ROI
• Build and apply machine learning models (e.g., churn prediction, probabilistic segmentation, response modeling) in applied business contexts
• Show expert proficiency in SQL, including complex querying across large-scale data warehouses
• Work fluently with cloud-based data environments, with preference for Google Cloud Platform (BigQuery)
• Partner with analytics and data engineering resources to automate datasets, reporting layers, and analytical workflows
• Oversee development and deployment of production-ready dashboards and visualization products, with Power BI strongly preferred
• Lead retail analytics focused on understanding the incremental impact of physical stores, including store-level and market-level incrementality analyses
• Evaluate the role of physical retail within the broader omnichannel ecosystem, including halo effects, customer acquisition, and cross-channel cannibalization or lift
• Partner with Retail and Finance stakeholders to assess store performance, test-and-learn results, and implications for expansion, optimization, or investment decisions
• Support Innovation analytics through market analysis, sizing, and performance assessment for new concepts, products, or business models
• Analyze customer trial, repeat behavior, and early cohort performance to inform go/no-go, scaling, and iteration decisions
• Evaluate potential cannibalization or substitution effects between new innovations and existing products or channels
• Partner with Brand stakeholders to analyze trial and repeat dynamics, customer adoption patterns, and brand performance over time
• Support campaign and launch readouts with a focus on driving sustained customer engagement and repeat behavior, not just short-term lift
• Lead Affiliate analytics focused on understanding Brand Consultant performance by cohort, including sales productivity and engagement
• Evaluate whether Affiliate initiatives, programs, and activities are driving incremental performance and positive impact within targeted Brand Consultant cohorts
• Develop and refine cohort frameworks to distinguish consultants who are actively building their business from those who are less engaged, and track movement between cohorts over time
• Partner with Affiliate leadership to assess the effectiveness of incentives and engagement efforts, and translate findings into clear recommendations
• Apply a strong understanding of financial concepts and workflows (e.g., operating margin, COGS, CAC, corporate planning) to analytical projects
• Closely work with Finance to ensure analytical outputs align with financial narratives and decision processes
• Support collaborative analyses that connect customer and channel behavior to financial outcomes
• Translate complex quantitative findings into clear, compelling narratives for non-technical audiences
• Integrate insights across multiple data sources to develop cohesive, decision-ready narratives rather than isolated point analyses
• Present insights and recommendations to senior leaders with confidence and clarity
• Navigate ambiguous problem spaces, distill complexity into core impact drivers, and communicate tradeoffs effectively
• Adapt communication style to stakeholders with varying levels of technical and quantitative fluency

Qualifications

• 7+ years of experience in analytics, data science, marketing analytics, or a related quantitative field
• Advanced degrees (Master’s or PhD) in a quantitative discipline may substitute for some years of experience
• Experience operating in consumer, retail, DTC, or omnichannel environments strongly preferred
• Bachelor’s degree required in a quantitative or STEM discipline, such as: Statistics, Operations Research, Data Science, Mathematics, Computer Science, or other quantitatively rigorous STEM fields
• Expert-level SQL proficiency, including work with large-scale data warehouses and automated data workflows
• Strong experience with cloud data platforms, preferably Google Cloud Platform
• Proven expertise in machine learning and statistical modeling, including: Churn and retention modeling, Predictive and probabilistic segmentation, Regression and classification techniques
• Strong statistical foundation, including: Hypothesis testing, Experimental design, Predictive modeling and inference
• Demonstrated experience deploying and maintaining production analytics and dashboards, with Power BI preferred
• Strong fluency in financial concepts and the ability to work effectively with Finance partners
• Exceptional written and verbal communication skills
• Demonstrated ability to extract insights from data and explain them plainly and persuasively to non-quantitative audiences
• Comfort presenting to executives and collaborating with stakeholders across varying levels of analytical sophistication