Data Scientist, RM Agentic Systems and Pricing Analytics

Choice Hotels International, Inc.; North Bethesda (MD); On-site; USD 120,000 - 160,000; Full time

Job summary

Choice Hotels International, Inc. is seeking a Data Scientist for the Revenue Management Agentic Systems and Pricing Analytics team.

You will use AI, data science, and revenue management to solve pricing, forecasting, and commercial performance questions at multiple levels, designing scalable models and decision-support tools to improve RevPAR and occupancy. You will work across RM, Pricing, Analytics, Product, and Technology to deploy agentic AI frameworks and validate models, with hands-on

Qualifications

• 2+ years of professional experience using structured and unstructured data to perform statistical analysis and build predictive models.
• Experience in predictive demand forecasting, price elasticity, dynamic pricing, causal inference, experimentation, and ML models.
• Demonstrated experience deploying AI agents or agentic workflows using Claude, CoWork, Copilot, OpenAI or comparable platforms.
• Experience with token throttling, hierarchical model routing, evaluation, prompt/version management, guardrails, monitoring, and responsible AI practices.
• High proficiency in Python, SQL, and/or R with ML methods, feature engineering, validation and testing.
• Experience with TensorFlow or PyTorch is a plus.

Responsibilities

• Design, build, test, and roll out agentic AI frameworks supporting RM and pricing workflows.
• Build and maintain data pipelines, feature stores, and model-ready datasets using SQL and Python.
• Implement responsible AI patterns for orchestration, evaluation, and monitoring of agents.
• Leverage Claude, CoWork, Copilot, and OpenAI to prototype, deploy, and scale agents in collaboration with tech teams.
• Define system health and model KPIs for AI-enabled RM solutions and measure impact.
• Develop predictive demand models and estimate price elasticity at brand, market, and hotel levels.

Skills

Python

SQL

R

Statistical analysis

Predictive modeling

Communication of insights

Tools

TensorFlow

PyTorch

Claude

OpenAI

CoWork

Git

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.
• 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.
• 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.
• 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,