Sr. Data Scientist, Econometrics

Planet Fitness•Boston, MA

1d•Hybrid

About The Position

The Senior Data Scientist, Econometrics develops advanced pricing and promotion analytics solutions, predictive models, optimization algorithms, and experimentation frameworks to help business leaders optimize pricing and promotion decisions globally. Reporting to the Director, Strategy Analytics, this role applies econometrics, statistical analysis, machine learning, AI, and optimization to complex elasticity and promotion incrementality problems. It partners with Strategy, Finance, Operations, Marketing, and Technology stakeholders and translates analytical findings into actionable business recommendations. The position follows a hybrid schedule, with regular in-person work at either the Boston, MA or Hampton, NH office. The hybrid schedule is Monday through Wednesday in the office, with Thursday and Friday optional work-from-home. Candidates must live within commuting distance of one of these offices; fully remote work is not available.

Requirements

Master's degree in Economics, Econometrics, Statistics, Data Science, Mathematics, Computer Science, Engineering, Analytics, Operations Research, or a related quantitative field.
At least 3 years of hands-on experience developing econometric and data science solutions for 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 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 models, 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.
Strong problem-solving skills and the ability to synthesize complex pricing, promotion, and business datasets into predictive insights and actionable recommendations.
Detail-oriented, efficient, and organized, with the ability to establish priorities and objectives.
Excellent presentation, written, and oral communication skills, with the ability to communicate effectively across all levels of the organization.
Ability to establish and maintain effective collaborative relationships with diverse individuals, internally and externally.
A commitment to learning, curiosity, teamwork, and a positive, can-do attitude.

Nice To Haves

Experience with econometrics and statistical libraries or tools such as statsmodels, linearmodels, scikit-learn, PyMC, R, or similar tools.
Experience with MLOps practices and tools such as MLflow, Kubeflow, Docker, or similar technologies for deploying, monitoring, and scaling machine learning models.

Responsibilities

Develop predictive and prescriptive econometric models for price elasticity, promotion incrementality, price optimization, promotional effectiveness, cannibalization, halo effects, demand forecasting, and margin optimization.
Propose, design, and build scalable, production-ready pricing and promotion solutions with Data Engineering and Technology for use in enterprise pricing and promotional planning.
Apply econometrics, causal inference, machine learning, AI, and optimization techniques to identify pricing and promotion opportunities and improve business performance.
Evaluate model performance and continuously improve econometric solutions through agile product development and ongoing validation.
Develop demand forecasts, scenario analyses, simulations, and optimization models to support pricing and promotion strategy, strategic planning, and investment decisions.
Design and evaluate pricing and promotion experiments and measurement methodologies to assess price elasticity, promotional lift, and strategy effectiveness.
Translate complex econometric analyses into actionable recommendations that guide executive decision-making.
Partner with Strategy, Finance, and Marketing to develop the econometrics and pricing and promotion analytics strategy and roadmap.
Collaborate with Finance, Marketing, Operations, and Technology stakeholders to solve business challenges using advanced econometric analytics.
Present analytical findings and recommendations clearly to technical and non-technical audiences.
Support enterprise growth initiatives through econometric modeling and data-driven insights.
Improve pricing and promotion data accessibility, analytical processes, automation, and model scalability.
Promote econometrics, AI, and data science best practices across the organization.

Benefits

Core medical, dental, vision, life, and disability coverage for eligible employees.
Supplemental accident, hospital, and critical illness coverage options.
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.
Employee engagement activities.
401(k) plan with safe harbor employer matching.
Employee stock purchase plan.
Annual corporate bonus incentive program based on company financial and personal performance.