Sr. Data Scientist, Marketing & Customer Analytics
Hampton, Rockingham County, New Hampshire, 03842, USA
Listed on 2026-11-06
-
IT/Tech
Data Analyst, Data Scientist, Machine Learning/ ML Engineer, Data Science Manager
Founded in 1992 in Dover, NH, Planet Fitness is one of the largest and fastest-growing franchisors and operators of fitness centers in the world by number of members and locations. As of March
31, 2026, Planet Fitness had approximately 21.5 million members and 2,909 clubs in all 50 states, the District of Columbia, Puerto Rico, Canada, Panama, Mexico, Australia and Spain.
The Company’s mission is to enhance people’s lives by providing a high-quality fitness experience in a welcoming, non-intimidating environment, which we call the Judgement Free Zone. Approximately 90% of Planet Fitness clubs are owned and operated by independent business owners.
At Planet Fitness, our purpose is to create a more connected and Judgement Free planet, where fitness and wellbeing are within reach for all. That commitment extends to our team members and how we work together.
Breaking Boundaries Together is how we bring our employee experience to life, creating a place where people can show up as themselves, explore what’s possible, continue to grow and achieve more together than they can alone. Guided by our PLANET Principles, we put people first, lead with authenticity and integrity, embrace change and thrive together.
For the past 30 years, we’ve helped millions of people in their fitness journey and revolutionized the industry along the way. And we’re just getting started!
OverviewThis role will be an integral part of building out our new data science team!
Reporting to the Director, Marketing Analytics & Data Science, the Senior Data Scientist, Marketing & Customer Analytics builds the core customer models that guide how we grow and keep our members, including lifetime value, next best action, attrition, and propensity models. You will lead the design and build of these models, partner with Data Engineering to put them into production, and see them used in everyday marketing decisions.
This role partners with Marketing, Technology, Data Engineering, and business stakeholders to apply statistical modeling, machine learning, and other advanced analytics to real questions about member behavior. In your first year, you can expect to design and build several of these core models and help set the roadmap for what comes next.
The ideal candidate has built and deployed customer predictive models in a marketing, CRM, or subscription setting, works well with engineering teams to get models into production, and can explain results clearly to non-technical leaders.
Experience with experimentation and measurement is a plus.
You will work in a collaborative environment on big, high-visibility projects that change how we grow and serve our members. This role follows a hybrid schedule and requires regular, in-person work at our Boston, MA or Hampton, NH office. Our hybrid model is M/T/W in office and TH/F are optional work-from-home. Candidates must reside within commuting distance of one of these locations.
Fully remote work is not available for this role.
Core Modeling and Data Science
- Designs and builds predictive and prescriptive models for lifetime value, next best action, attrition and winback, conversion propensity, and segmentation.
- Works with Data Engineering and Technology to move models into production and embed them in standard marketing decision processes.
- Translates complex analytical outputs into actionable recommendations for Marketing and business leaders.
- Monitors model performance and improves models over time through regular retraining and iteration.
Measurement and Experimentation
- Designs and analyzes experiments, including A/B and incrementality tests, to validate the impact of models and marketing programs.
- Develops frameworks to evaluate marketing effectiveness and customer behavior.
- S…
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).