Director, Data and Analytics

Madison Reed•San Francisco, CA

12h•$190,000 - $210,000•Remote

About The Position

The Director, Data & Analytics will own advanced analytics and insights for Madison Reed. This leader turns the company’s open questions about customer behavior into models and analyses that change what the business does next. You will lead the analytics practice on a centralized data team that serves every part of the business: DTC, Hair Color Bar, Amazon and wholesale, plus the marketing and product analytics that support them. You own the measurement that guides where we spend, how we keep our members, and what we build. The ideal candidate is a hands-on analytics leader who can define the right measurement approach, defend a model, and then sit with a channel GM and explain in plain language what the result means for their plan.

Requirements

Proven ability to lead a team to translate business questions into verifiable hypotheses, define analyses that test them, and generate actionable insights based on the findings.
Strong business and operational acumen to recognize patterns, connections and relationships across variables. Make the connections across data sets to help others understand the broader picture.
Track record of earning a standing seat with business partners, so analytics is in the room when the decision gets made rather than working from a request queue.
Ability to bring data to life and inspire action with clarity and simplicity; experience successfully communicating with senior or C-level executives in a clear and concise way.
High affinity and intellectual curiosity in the fast evolving world of AI, with a habit of adopting Claude and similar tools to improve efficiency and go deeper on insight.
Deep analytical abilities and experience improving performance in key operating metrics, specifically but not limited to acquisition, retention and monetization insights, customer segmentation, and pricing.
Comfortable holding a position under executive questioning, and direct about what the data does not support.
Self-motivated and proactive, taking initiative, going beyond the call of duty, and taking accountability for the business’s performance.
High degree of initiative, integrity and curiosity for understanding patterns and behaviors through the use of data.
Experience working in a matrixed organization across executive management, business leads, developers, and marketing teams to successfully meet deadlines in a fast-paced, rapidly changing environment.
Proven ability to remain calm and composed under uncertainty.
Degree in Quantitative field or commensurate experience (Statistics, Applied Mathematics, Applied Analytics, Operations Research, Econometrics, Computer Science, Applied Science).
8+ years’ experience in analytics and insights, with 3+ years leading and mentoring analysts.
Experience in multi-channel consumer business, ideally with a subscription or membership model.
Hands-on experience with statistical and machine learning techniques (regression, classification, clustering, churn and survival models) and the judgment to know when a simpler approach is better.
Advanced SQL, plus Python or R for analysis and modeling.
Hands-on dbt experience. You author and review models yourself rather than only querying their output.
Experience owning a BI environment at scale, ideally Looker, including writing and reviewing LookML yourself, plus a notebook environment such as Hex.
Product analytics experience on a dedicated platform (Amplitude, Heap or similar), and a track record supporting experiment analysis and decision-making.
Expertise in ecommerce marketing analytics: SEM, SEO, Remarketing, Social, event-triggered push campaigns, site personalization. Experience with multi-touch attribution (MTA) and marketing mix modeling (MMM) solution implementation, usage, socialization and activation.
Understanding of A/B testing as well as knowledge of how to identify the key metrics that measure and drive long-term health of the business.

Nice To Haves

Consulting or customer insights experience a plus.

Responsibilities

Own rigorous end-to-end analytics projects, moving from data exploration to business implementation and measurable ROI.
Apply data science and machine learning to customer LTV, churn and retention prediction, customer segmentation, and omnichannel impact.
Own channel performance, multi-touch attribution and marketing mix modeling, incrementality testing, and the analysis behind paid and organic spend decisions.
Partner with our channel GMs, Digital Product, Engineering, Marketing, Finance and Retail to embed data-informed decision-making into their core roadmaps.
Place your analysts directly in business meetings so they own the relationship with their partners rather than working from a request queue.
Own our product analytics platform (Amplitude), including event taxonomy, funnel analysis, and the behavioral segmentation that feeds personalization work.
Partner with Product and business teams to define success metrics, advise on statistical rigor, and own the analysis and readouts that turn test results into decisions.
Partner with e-commerce and lifecycle marketing on cohort retention, subscription health, and the levers that move repeat purchase.
Build in dbt and Looker as needed. Author and review dbt models and LookML so the metrics behind your analysis are governed, tested and reusable rather than living in one-off queries.
Translate recurring business questions into governed metrics and self-service dashboards in Looker and Hex.
Work within our standard, where transformation logic lives in dbt and Looker stays a thin semantic layer.
Lead and mentor a team of analytics engineers, fostering a culture of curiosity and accountability.
Set the analytical standard for the team: how you validate a result, when a caveat belongs in the summary, and when a number is not ready to present.