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Choice Hotels

Franchises hotels and manages accommodations

Data Scientist - RM Agentic Systems and Pricing Analytics

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeNorth Bethesda, MD, USA

About the Job

Requirements

  • At least 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 and 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.
  • 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.
  • Ability to draw conclusions from data and translate analytical 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.
  • Ability to build trust and work across departments and disciplines to design practical solutions.
  • 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.

Responsibilities

  • 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 and 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 Revenue Management 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 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 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 Revenue Management 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 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.

Desired Qualifications

  • Experience with machine-learning frameworks or libraries such as 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.

About the Company

Choice Hotels

Franchises hotels and manages accommodations

Choice Hotels International runs a global hotel franchising business. It works by letting property owners use its brand names in exchange for fees, providing centralized reservation systems, marketing, loyalty programs, and standardized quality guidelines while the owners manage daily operations. Unlike many competitors that own hotels, Choice Hotels grows mainly through franchising and leases, supported by a tiered brand lineup and a long history from a regional referral network to a worldwide platform. Its goal is to expand its franchise network globally while keeping consistent guest experiences and delivering value to guests and franchisees through trusted brands and scalable operations.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Rockville, MD
Founded
1941

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