About Us

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!

Overview

Reporting to the Director, Strategy Analytics, the Senior Data Scientist, Econometrics develops advanced pricing and promotion analytics solutions, predictive models, optimization algorithms, and experimentation frameworks that enable business leaders to optimize pricing and promotion decisions globally.

This role partners with Strategy, Finance, Operations, Marketing, and Technology stakeholders to apply econometrics models, statistical analyses, machine learning, AI, and optimization techniques to solve complex elasticity and promotion incrementality business problems.

The ideal candidate combines proven expertise in econometrics techniques, predictive modeling, price and promotion optimization, and enterprise analytics with the ability to translate complex price and promotion insights into actionable business recommendations.

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.

Responsibilities

Advanced Econometrics, Data Science & Measurement

Develops predictive and prescriptive econometric models supporting price elasticity, promotion incrementality, price optimization, promotional effectiveness, cannibalization, halo effects, demand forecasting, and margin optimization.
Proposes, designs, and builds scalable, production-ready pricing and promotion solutions in collaboration with Data Engineering and Technology that become embedded in enterprise pricing and promotional planning decision processes.
Applies advanced econometrics, causal inference, machine learning, AI, and optimization techniques to identify pricing and promotion opportunities and improve business performance.
Evaluates model performance and continuously improves econometric solutions through agile product development and ongoing validation.
Develops demand forecasting models, scenario analyses, simulations, and optimization models that support pricing and promotion strategy, strategic planning, and investment decisions.
Designs and evaluates pricing and promotion experiments and measurement methodologies to assess price elasticity, promotional lift, and pricing and promotion strategy effectiveness.
Translates complex econometric analyses into actionable recommendations that guide executive decision-making.

Cross-Functional Partnership

Works hand in hand with Strategy, Finance, and Marketing partners to develop the econometrics and pricing and promotion analytics strategy and roadmap.
Collaborates with Finance, Marketing, Operations, and Technology stakeholders to solve complex business challenges using advanced econometric analytics.
Presents analytical findings and recommendations clearly to technical and non-technical audiences.
Supports enterprise growth initiatives through advanced econometric modeling and data-driven insights.
Improves pricing and promotion data accessibility, analytical processes, automation capabilities, and model scalability.
Promotes econometrics, AI, and data science best practices across the organization.

Qualifications

Master's degree in Economics, Econometrics, Statistics, Data Science, Mathematics, Computer Science, Engineering, Analytics, Operations Research, or a related quantitative field.
3+ years of hands-on experience developing econometric and data science solutions supporting pricing strategy, promotion effectiveness, or revenue optimization.
Demonstrated experience developing predictive models and advanced econometric solutions for price elasticity, promotion incrementality, demand forecasting, price and promotion optimization, customer response modeling, or related pricing and promotion applications.
Strong understanding of econometrics, causal inference, machine learning, optimization techniques, predictive modeling, and pricing and promotion experimentation methodologies.
Experience with econometric modeling techniques such as regression, panel data, time series, Bayesian hierarchical, difference-in-differences, and instrumental variable methods, or similar approaches.
Proficiency in Python, SQL, and modern analytics platforms such as Snowflake, Databricks, or similar cloud-based data environments.
Experience with econometrics and statistical libraries and tools such as statsmodels, linearmodels, scikit-learn, PyMC, R, or similar tools is highly desired.
Experience with MLOps practices and tools such as MLflow, Kubeflow, Docker, or similar technologies to deploy, monitor, and scale machine learning models is a plus.
Strong problem-solving skills with the ability to synthesize complex pricing, promotion, and business datasets into predictive insights and actionable recommendations.
Extremely detail-oriented, efficient, and organized with an exceptional ability to establish priorities and objectives
Excellent presentation and written and oral communication skills along with the ability to communicate effectively across all levels of the organization
Able to establish and maintain effective, collaborative work relationships with diverse individuals, internally and externally
Dedicated learner with a natural curiosity for consistent growth
Cooperative team player with an upbeat, positive, “can-do” attitude!

Perks

Planet Fitness cares about you and your well-being. We offer a comprehensive benefits package to eligible employees which includes the core medical, dental, vision, life and disability as well as supplemental accident, hospital and critical illness coverage options. In addition, we are proud to offer eligible employees a generous time off program (including volunteer time), childcare reimbursement, paid parental leave, pet care reimbursement, tuition reimbursement, free Black Card membership, learning and development programs and a whole host of engagement activities. We offer a 401(k) Plan with safe harbor employer matching and an employee stock purchase plan.

The salary for MA-based and NH-based employees hired into this role will be aligned with the range below. This is a good faith estimate, and the amount of base salary will correspond with a candidate’s professional experience, qualifications and internal equity.

Annual Base Salary Range: $130,000-$170,000

This role is also eligible to participate in an annual corporate bonus incentive program based on company financial and personal performance.

Note to Applicants: We have been made aware of an increasing number of hiring fraud schemes across numerous platforms. Planet Fitness never requires advance payments of any kind for computer equipment or any other purpose at the start of employment. Any request for you to provide payment information during the application process is part of a fraud scheme. Further, we recommend that you do not provide sensitive personal information (SSN, DOB, driver’s license number) as part of the initial application process.

About Us

Overview

Responsibilities

Qualifications

Perks

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Planet Fitness

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Sr. Data Scientist, Econometrics