Data Scientist, RM Agentic Systems and Pricing Analytics

Choice Hotels • North Bethesda, MD

11d • Hybrid

About The Position

As a Data Scientist on Choice Hotels’ Revenue Management Agentic Systems and Pricing Analytics team, this individual-contributor role applies AI, data science, and revenue management expertise to pricing, forecasting, and commercial performance questions at the brand, market, and hotel/property levels. The role designs, builds, tests, and deploys agentic AI frameworks for pricing analysis, demand forecasting, elasticity measurement, dynamic pricing recommendations, and causal inference analytics. It partners with Revenue Management, Pricing, Analytics, Product, and Technology teams to turn business questions into scalable models, agents, and decision-support tools that improve metrics such as RevPAR, RPI, ADR, occupancy, and competitive price position. The position also develops predictive models, evaluates pricing and promotional strategies, and supports the modernization of revenue management workflows through responsible use of AI platforms.

Requirements

• At least 2 years of professional experience using structured and unstructured data for statistical analysis, predictive modeling, and business insights.
• Hands-on experience developing predictive demand forecasting, price elasticity, dynamic pricing, causal inference, experimentation, and machine learning models.
• Demonstrated experience building, deploying, or operationalizing AI agents or agentic workflows using Claude, CoWork, Copilot, OpenAI, or comparable enterprise AI platforms.
• Experience with token throttling, hierarchical model routing, model evaluation, prompt/version management, guardrails, monitoring, and responsible AI practices for production or business-facing agents.
• High proficiency in Python, SQL, and/or R, including supervised and unsupervised learning, statistical modeling, feature engineering, validation, and testing.
• Professional experience creating data visualizations and executive-ready analytics using Tableau, Power BI, Excel, Matplotlib, or Seaborn.
• Proficiency in Microsoft Excel, PowerPoint, and business intelligence tools.
• Strong strategic and critical thinking, including the ability to draw conclusions from data and translate findings into revenue management and pricing recommendations.
• Ability to decompose Revenue Management and Pricing questions into analytical, AI-agent, and model-development use cases with clear success metrics.
• Strong communication, storytelling, teamwork, collaboration, organization, and stakeholder management skills.
• Strong interpersonal skills and the ability to build trust and work across departments and disciplines.
• Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, Business Analytics, Information Systems, or a related quantitative field, or an equivalent combination of education and relevant work experience.

Nice To Haves

• Experience with TensorFlow, PyTorch, Keras, Scikit-Learn, LangChain, LlamaIndex, or Semantic Kernel.
• Familiarity with Microsoft Copilot and M365 productivity workflows.
• Knowledge of pricing, revenue management, hotel revenue strategy, RevPAR, RPI, ADR, occupancy, segmentation, and distribution principles.
• Master’s degree in a related quantitative field.

Responsibilities

• Design, develop, test, and roll out agentic AI frameworks supporting Revenue Management and pricing workflows, including agents for pricing diagnostics, demand signals, competitive insights, and recommendation support.
• Build and maintain data pipelines, feature stores, model-ready datasets, and analytical tools using SQL, Python, and approved enterprise data sources.
• Implement responsible AI patterns for agent orchestration, evaluation, monitoring, prompt and version control, guardrails, token throttling, and hierarchical model routing.
• Use platforms such as Claude, CoWork, Copilot, and OpenAI to prototype, deploy, and scale agents with Technology, Product, and Analytics teams.
• Create system health and model performance KPIs for AI-enabled revenue management solutions, including adoption, latency, accuracy, quality, cost efficiency, and business impact.
• Develop and validate short- and long-term predictive demand forecasting models at brand, market, and hotel/property levels.
• Estimate price elasticity, demand sensitivity, booking pace, segmentation behavior, and competitive response to inform pricing strategy and rate recommendations.
• Apply causal inference, experiment design, A/B testing, uplift measurement, and statistical validation to assess pricing, promotional, and revenue management initiatives.
• Analyze historical and forward-looking data to identify patterns, trends, and revenue opportunities that improve RevPAR, RPI, ADR, and occupancy.
• Translate model outputs into recommendations, visualizations, and executive-ready insights for Revenue Management and Pricing stakeholders.
• Conduct competitive analysis using internal and external market signals to guide pricing strategy.
• Identify opportunities to improve revenue, price position, and revenue capture through scalable pricing analytics and decision support.
• Partner with Revenue Management, Pricing, Brand, Product, Operations, and Technology teams to prioritize use cases based on business value, feasibility, and adoption impact.
• Develop business cases, analytical readouts, implementation plans, and stakeholder materials for commercial decisions and revenue management transformation initiatives.
• Manage intake of analytical and AI-agent requests, define success metrics, and support deployment, training, change management, and post-launch measurement.

Benefits

• Medical, dental, and vision coverage.
• Paid leave and time off for holidays, vacation, personal, family, volunteer, sick, jury duty, bereavement, military, and religious observance.
• Financial benefits for retirement and health savings.
• Employee recognition programs.
• Discounts at Choice hotels worldwide.
• Annual bonus eligibility under Choice’s Management Incentive Plan (MIP).

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level