Sr. Geospatial Data Scientist

Planet Fitness•Boston, MA

11h•$125,000 - $150,000•Hybrid

About The Position

Reporting to the Director, Geospatial Analytics & Data Science, the Senior Geospatial Data Scientist develops advanced geospatial analytical solutions, predictive models, optimization algorithms, and experimentation frameworks that enable business leaders to optimize market expansion, site selection, member growth, and business performance. This role partners with Strategy, Real Estate, Finance, Operations, Marketing, and Technology stakeholders to apply geospatial analytics, statistical modeling, machine learning, AI, and optimization techniques to solve complex location-based business problems. The ideal candidate combines proven expertise in geospatial data science, predictive modeling, spatial optimization, and enterprise analytics with the ability to translate complex spatial 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.

Requirements

Master's degree in Data Science, Geography, GIS, Statistics, Mathematics, Computer Science, Economics, Engineering, Analytics, Operations Research, or a related quantitative field.
3+ years of hands-on experience developing geospatial data science solutions supporting business strategy, location analytics, or market optimization.
Demonstrated experience developing predictive models and advanced geospatial analytical solutions for site selection, trade area analysis, market potential, demand forecasting, spatial optimization, customer segmentation, or related location intelligence applications.
Strong understanding of spatial statistics, machine learning, optimization techniques, predictive modeling, and geospatial experimentation methodologies.
Experience with GIS platforms such as ArcGIS, Esri, CARTO, Mapbox, QGIS, or similar geospatial technologies.
Proficiency in Python, SQL, and modern analytics platforms such as Snowflake, Databricks, or similar cloud-based data environments.
Experience with geospatial Python libraries such as GeoPandas, Shapely, NetworkX, Rasterio, PySAL, 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 spatial 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!

Nice To Haves

Experience with geospatial Python libraries such as GeoPandas, Shapely, NetworkX, Rasterio, PySAL, 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.

Responsibilities

Develops predictive and prescriptive geospatial models supporting market expansion, site selection, trade area analysis, cannibalization, white space identification, member demand forecasting, and location optimization.
Proposes, designs, and builds scalable, production-ready geospatial solutions in collaboration with Data Engineering and Technology that become embedded in enterprise real estate and market planning decision processes.
Applies advanced spatial statistics, machine learning, AI, and optimization techniques to identify market opportunities and improve business performance.
Evaluates model performance and continuously improves geospatial solutions through agile product development and ongoing validation.
Develops geospatial forecasting models, scenario analyses, simulations, and optimization models that support strategic planning and investment decisions.
Designs and evaluates geospatial experiments and measurement methodologies to assess market performance, trade area dynamics, and location strategy effectiveness.
Translates complex geospatial analyses into actionable recommendations that guide executive decision-making.
Works hand in hand with Strategy, Real Estate, and Operations partners to develop the geospatial analytics and data science strategy and roadmap.
Collaborates with Finance, Marketing, Operations, and Technology stakeholders to solve complex business challenges using advanced spatial analytics.
Presents analytical findings and recommendations clearly to technical and non-technical audiences.
Supports enterprise growth initiatives through advanced geospatial modeling and data-driven insights.
Improves geospatial data accessibility, analytical processes, automation capabilities, and model scalability.
Promotes geospatial analytics, AI, and data science best practices across the organization.