Manager of Analytics

Rodan and Fields Beauty, LLC•San Ramon, CA

4d•Hybrid

About The Position

Rodan + Fields is seeking a highly skilled Manager, Analytics to lead advanced analytics in support of Retail, Brand, Innovation and Affiliate channels. This role combines deep technical expertise, strong business judgment, and clear executive communication to translate complex data into actionable insights that inform commercial decision‑making. The Manager will act as the primary analytics partner for assigned business areas, owning analytical problem framing, insight development, and performance storytelling, while partnering closely with the Senior Manager on enterprise standards, customer frameworks, and strategic priorities. This role serves as the primary owner of advanced analytical execution for its channels, including model development, experimentation, and ongoing iteration, while partnering with the Senior Manager for enterprise alignment and executive application. This is a manager‑level individual contributor role (no direct people management initially), designed for an analytically rigorous leader who can operate independently across complex problem spaces and communicate effectively with both technical and non‑technical audiences.

Requirements

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
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

Nice To Haves

Experience operating in consumer, retail, DTC, or omnichannel environments strongly preferred

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
Demonstrate 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
Partner closely 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