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FabFitFun

Lead Data Analyst

FabFitFun, Los Angeles, California, United States, 90079


About the Role:

As a Lead Data Analyst, you will be pivotal in shaping data-driven strategies that enhance the experiences we offer our members. Your insights will support business growth, inform product decisions, and drive efficiencies across our e-commerce subscription platform. You will collaborate closely with various teams, including Marketing, Product, Merchandising, Engineering, and Finance, to provide actionable data insights that influence decision-making and future roadmaps. This role focuses on leveraging advanced analytics and statistical techniques to support personalization, acquisition, retention, and growth strategies.

At FabFitFun, you will have the opportunity to make a significant impact by guiding the analytics that support our growth, retention, and customer satisfaction. You will own data initiatives from end to end and help create a lasting influence on the way we make data-driven decisions.

Location:

FabFitFun is based in Beverly Hills, CA. This position is expected to work hybrid (3 days) from our HQ and is not eligible for remote.

Key Responsibilities:

Data Leadership:

Provide strategic direction using data insights to shape business initiatives, identify growth opportunities, and address potential challenges. Work closely with leadership to align data initiatives with business objectives.

Advanced Analytics & Statistical Analysis:

Apply rigorous analytical methods to drive key business decisions. Lead efforts in hypothesis testing, A/B testing, regression analysis, and forecasting to inform product and marketing strategies.

E-commerce Focus:

Leverage your experience in e-commerce to develop actionable insights that improve customer acquisition, retention, and overall user experience in a subscription-based model.

Business Intelligence (BI) Tools:

Build, maintain, and improve data products including dashboards, reports, and ad hoc analyses using Tableau and Snowflake to enable data-driven decision-making across the company.

Cross-functional Collaboration:

Partner with teams from Engineering, Marketing, and Product to influence strategy and drive execution. Build strong relationships to align business needs with data initiatives.

People Leadership:

Mentor and inspire a team of analysts, fostering a data-driven culture. Guide junior analysts on best practices and technical expertise, upskilling the team to enhance overall impact.

Communication & Storytelling:

Translate complex data sets into compelling stories. Present insights clearly to stakeholders at all levels, providing actionable recommendations that align with business goals.

Minimum Qualifications:

Bachelor's degree in Statistics, Mathematics, Computer Science, or a related quantitative field.

5+ years of experience in data analytics or related fields, with 2+ years providing technical support and guidance to teams.

Proven experience in an e-commerce environment, preferably subscription-based business models.

Expertise in advanced analytics, statistical methods, and experience with tools such as Tableau, Snowflake, SQL, Python, or R.

Strong ability to communicate both technical details and high-level business strategies.

Preferred Qualifications:

Master’s degree or higher in a quantitative field.

Hands-on experience with machine learning, A/B testing, and experimental design.

Deep knowledge of e-commerce KPIs, personalization techniques, and subscription models.

Strong leadership and stakeholder management skills with the ability to influence at various organizational levels.

The expected base salary range for this position is $135K to $160K + bonus. The compensation package will also include an initial equity grant, in addition to a range of generous medical, dental, vision and other perks & benefits. Compensation decisions are determined using a variety of job-related factors such as skill set, geographic location, market demands, experience, and education / certifications. If we extend an offer for employment, we will consider all individual qualifications.

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