Data Scientist, RM Agentic Systems and Pricing Analytics at Choice Hotels

Job description

JOB SUMMARY: As a Data Scientist for Choice s Revenue Management Agentic Systems and Pricing Analytics team, you will use AI, data science, and revenue management expertise to solve pricing, forecasting, and commercial performance questions at the brand, market, and hotel/property level. You will design, build, test, and deploy agentic AI frameworks that support pricing analysis, demand forecasting, elasticity measurement, dynamic pricing recommendations, and causal inference analytics. You will partner with Revenue Management, Pricing, Analytics, Product, and Technology teams to convert business questions into scalable models, agents, and decision-support tools that improve key KPIs such as RevPAR, RPI, ADR, occupancy, and competitive price position. This individual-contributor role will develop predictive models, evaluate pricing and promotional strategies, and help modernize RM workflows through the responsible use of AI platforms such as Claude, Copilot, and OpenAI. The role requires hands-on experience with model development, validation, agent rollouts, and production-ready analytics that improve pricing strategy and revenue outcomes. RESPONSIBILITIES: Agentic AI Systems, Model Operations and Data Engineering Design, develop, test, and roll out agentic AI frameworks that support 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/version control, guardrails, token throttling, and hierarchical model routing. Use AI platforms such as Claude, CoWork, Copilot, and OpenAI to prototype, deploy, and scale agents in partnership with Technology, Product, and Analytics teams. Create system health and model performance KPIs for AI-enabled RM solutions, including adoption, latency, accuracy, quality, cost efficiency, and business impact. Predictive Forecasting, Elasticity, Dynamic Pricing and Causal Analytics Develop and validate predictive demand forecasting models for short-term and long-term revenue management planning at the brand, market, and hotel/property level. 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 evaluate pricing, promotional, and RM 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 clear recommendations, visualizations, and executive-ready insights for Revenue Management and Pricing stakeholders. Revenue Management Strategy, Competitive Analysis and Stakeholder Delivery Perform competitive analysis using internal and external market signals to guide pricing strategy at the brand, market, and hotel/property level. Identify opportunities to improve RevPAR, RPI, ADR, occupancy, price position, and revenue capture through scalable pricing analytics and RM 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 that support commercial decisions and RM transformation initiatives. Manage intake of analytical and AI-agent requests, define success metrics, and support deployment, training, change management, and post-launch measurement. QUALIFICATIONS: Employment Experience 2 years of professional experience using structured and unstructured data to perform statistical analysis, build predictive models, and provide 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. Technical Skills High proficiency in Python, SQL, and/or R, with experience using supervised and unsupervised learning methods, statistical modeling, feature engineering, validation, and testing. Experience with ML frameworks or libraries such as TensorFlow, PyTorch, Keras, Scikit-Learn, LangChain, LlamaIndex, or Semantic Kernel is a plus. Professional experience creating data visualizations and executive-ready analytics using Tableau, Power BI, Excel, Matplotlib, or Seaborn. Proficient in Microsoft Excel, PowerPoint, and business intelligence tools; familiarity with Microsoft Copilot and M365 productivity workflows preferred. Additional Skills & Competencies Strong strategic and critical thinking skills, with the ability to draw conclusions from data and translate analytical findings into RM 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, with the ability to build trust and work across departments and disciplines to design practical solutions. Knowledge of pricing, revenue management, hotel revenue strategy, RevPAR, RPI, ADR, occupancy, segmentation, and distribution principles is strongly preferred. Education Requirements 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. A master’s degree in a related quantitative field is preferred. COMPENSATION & SALARY RANGE: The salary range for this position is $114,907-135,000. This role is also eligible for an annual bonus under Choice’s Management Incentive Plan (MIP). Pay ranges listed are what Choice Hotels reasonably expects to pay. Actual pay may be higher or lower and ranges may be adjusted in the future. Pay positioning within the range is influenced by factors including—but not limited to—education, experience, skills, certifications, performance, geographic location, business needs, seniority, and travel requirements. WORK LOCATION & HYBRID SCHEDULE: This position is based at Choice Hotels International s corporate headquarters in North Bethesda, Maryland. Associates follow a hybrid work schedule, working in the office Monday through Thursday and remotely on Fridays. RELOCATION & SPONSORSHIP: Please note that relocation assistance is not available for this position. Additionally, Choice Hotels is not able to provide employment visa sponsorship now or in the future for this role. Choice prioritizes our associate wellbeing by offering a comprehensive benefits program that is both competitive and flexible to help you achieve your wellbeing goals - here are just a few: Competitive compensation and benefits, including medical, dental, and vision coverage Leave and paid 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 About Choice Choice Hotels International, Inc. (NYSE: CHH), is one of the largest lodging franchisors in the world. With 7,500 hotels in 45 countries and territories, we offer a range of high-quality lodging options in the upper upscale, upper midscale, midscale, extended stay, and economy segments. We’re the hotel company for those who choose to bet on themselves — the striver, the dreamer, the entrepreneur — because that’s who we are, too. At Choice, we are united by the simple belief that tomorrow will be even better than today — for associates, our company, and our franchisees. At our worldwide corporate headquarters in North Bethesda, Maryland, at our technology center in Scottsdale, Arizona, and through our associates around the globe, every voice is heard and every idea is listened to, no matter what area of the company they come from. We are united in supporting the entrepreneurial dreams of our thousands of franchise owners, which propels us forward — giving our work at Choice a purpose larger than our business. Our corporate office locations: North Bethesda, MD — Located at Pike & Rose , our worldwide headquarters is less than 15 miles from Washington, D.C., one block away from the North Bethesda Metro station, with easy access to I-495, complimentary parking, electronic charging stations, restaurants and retail. Scottsdale, AZ — Located at the northwest corner of Loop 101, the Scottsdale office is home to our technology, eCommerce and customer service organizations, with easy access to complimentary parking, electronic charging stations, restaurants and retail. Minneapolis, MN — Select roles are based in our Minneapolis office on Highway 394, near the intersection with Highway 100, only five minutes from downtown. Field/Remote — Select roles designated as field/remote will require associates to work from a home office, connecting virtually with Choice team members and leadership on Zoom, with possible required travel depending on the role. Choice’s Cultural Values Welcome and Respect Everyone | Be Bold | Be Quick | Listen | Be Curious | Show Integrity Choice’s Leadership Principles Act with Intention | Lead with Authenticity | Grow & Deliver

Requirements

Must-haves

Agentic AI Systems, Model Operations and Data Engineering
Design, develop, test, and roll out agentic AI frameworks that support 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/version control, guardrails, token throttling, and hierarchical model routing.
Use AI platforms such as Claude, CoWork, Copilot, and OpenAI to prototype, deploy, and scale agents in partnership with Technology, Product, and Analytics teams.
Create system health and model performance KPIs for AI-enabled RM solutions, including adoption, latency, accuracy, quality, cost efficiency, and business impact.
Predictive Forecasting, Elasticity, Dynamic Pricing and Causal Analytics
Develop and validate predictive demand forecasting models for short-term and long-term revenue management planning at the brand, market, and hotel/property level.
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 evaluate pricing, promotional, and RM 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 clear recommendations, visualizations, and executive-ready insights for Revenue Management and Pricing stakeholders.
Revenue Management Strategy, Competitive Analysis and Stakeholder Delivery
Perform competitive analysis using internal and external market signals to guide pricing strategy at the brand, market, and hotel/property level.
Identify opportunities to improve RevPAR, RPI, ADR, occupancy, price position, and revenue capture through scalable pricing analytics and RM 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 that support commercial decisions and RM transformation initiatives.
Manage intake of analytical and AI-agent requests, define success metrics, and support deployment, training, change management, and post-launch measurement.
Employment Experience
2 years of professional experience using structured and unstructured data to perform statistical analysis, build predictive models, and provide business insights.

Nice-to-haves

Experience with ML frameworks or libraries such as TensorFlow, PyTorch, Keras, Scikit-Learn, LangChain, LlamaIndex, or Semantic Kernel is a plus.
Proficient in Microsoft Excel, PowerPoint, and business intelligence tools; familiarity with Microsoft Copilot and M365 productivity workflows preferred.
Knowledge of pricing, revenue management, hotel revenue strategy, RevPAR, RPI, ADR, occupancy, segmentation, and distribution principles is strongly preferred.
A master’s degree in a related quantitative field is preferred.

Application prep

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Keywords to mirror

aisqlpythonmachine learningml

Platform: workday
Effort: long

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