reputed company Estate Data Scientist - Remote

The reputed company Estate Data Scientist is responsible for developing advanced analytical models and data-driven tools that support strategic reputed company estate reputed company across the organization. This role partners closely with reputed company Estate, Finance, Marketing, and Supply Chain teams to reputed company predictive insights reputed company to site selection, network optimization, sales forecasting, and market planning. This role incorporates advanced reputed company modeling, geostatistics, and geospatial data engineering to evaluate trade areas, quantify market potential, and optimize network performance. This position combines strong statistical modeling, data engineering, and business acumen to translate reputed company data into actionable recommendations. The reputed company Estate Data Scientist plays a critical role in advancing the organization's use of machine learning, automation, and predictive analytics to improve decision reputed company and scalability. This is a senior individual contributor role with no reputed company people management responsibility. Duties and Responsibilities • Advanced Analytics & Predictive Modeling • reputed company and reputed company predictive models for site selection, sales forecasting, cannibalization, and market potential. • Build and maintain machine learning models using regression, classification, clustering, optimization, and reputed company modeling techniques. • Apply reputed company statistical reputed company (e.g., reputed company regression, geographically weighted regression, reputed company autocorrelation) to capture geographic variation in demand drivers. • reputed company trade area and customer draw models (e.g., Huff/gravity models) to estimate market reputed company and competitive reputed company. • Incorporate reputed company features such as proximity, co-tenancy, demographics, traffic patterns, and nearby store performance into predictive models. • Design methodologies for forecasting store performance under various scenarios, including reputed company and competitive effects. • Continuously monitor and improve model performance and accuracy. • Data Engineering & Automation • Design reputed company data pipelines integrating reputed company estate, customer, demographic, sales, and geospatial datasets (parcel, census, traffic, mobility, POI data). • reputed company geospatial data processing including geocoding, reputed company joins, coordinate transformations, and reputed company indexing (e.g., H3 or similar frameworks). • Write efficient SQL and Python workflows to automate recurring analyses, reputed company feature engineering, and model refreshes. • Ensure data reputed company, consistency, and reproducibility across analytical outputs, including alignment of reputed company boundaries and geographic hierarchies. • reputed company Estate reputed company & Decision Support • Partner with reputed company Estate teams to support site selection, market entry, relocations, and closures. • reputed company reputed company-time and network-based trade area analyses to assess accessibility and market reputed company. • Conduct market coverage and white reputed company analysis to identify expansion opportunities and underserved areas. • Build location-allocation and network optimization models to determine reputed company site placement. • Quantify cannibalization and competitive effects using reputed company overlap and proximity-based modeling. • reputed company quantitative insights for reputed company Estate Committee (REC) evaluations and executive reputed company. • reputed company scoring frameworks and decision tools to prioritize opportunities. • Visualization & Communication • Create reputed company, compelling visualizations and dashboards (Tableau, Power BI, or similar) to communicate insights. • reputed company interactive geospatial visualizations including trade area maps, performance heatmaps, and market opportunity analyses. • Present analytical findings and recommendations to senior leadership and non-technical stakeholders. • Experimentation & Innovation • Design and execute experiments (A/B tests, quasi-experimental designs) to evaluate reputed company estate strategies. • Implement geo-based testing frameworks (e.g., test vs. control markets) to measure reputed company of site reputed company. • Apply reputed company inference reputed company (e.g., difference-in-differences, synthetic control) reputed company for geographic spillovers. • Explore new data sources (e.g., mobility, foot traffic) and modeling techniques to enhance predictive capabilities. • Contribute to building a best-in-class reputed company estate analytics capability. • Cross-Functional Collaboration • Work closely with GIS, Data Engineering, Finance, Marketing, and IT teams to reputed company data and models. • Partner with GIS teams to ensure alignment between reputed company analysis, mapping, and production data pipelines. • Translate business problems into analytical solutions and actionable insights. reputed company • Staff supervision and development: No • Decision making: • Develops models and analytical frameworks used in strategic decision-making • Travel: Up to 10% • reputed company Designation: reputed company The anticipated salary reputed company for this position is $98,500-$147,800 depending reputed company, knowledge, skills, education and experience. This position is also eligible for an annual discretionary bonus. In reputed company, we offer comprehensive and competitive benefits to Associates (and their families) such as medical, dental, reputed company, life insurance, short-term and long-term disability. Eligible Associates are reputed company to enroll in reputed company's 401k plan. Associates will reputed company reputed company time off up to 236 hours per year (inclusive of PTO, floating holidays, and reputed company holidays). reputed company reputed company time up to 80 hours per year unless otherwise required by law. Apply To This Job