Principal Operations Research Scientist - 90028548 - Washington

Amtrak•Washington, DC

7d•$124,600 - $161,352•Onsite

About The Position

The Principal Operations Research Scientist – Revenue Management Systems (RMS) is a senior individual contributor role reporting to the Director, Revenue Products and Business Planning within the Pricing, Revenue Management, Sales and Distribution (PRMSD) organization at Amtrak. This role combines advanced analytical reasoning, operations research expertise, and system-level thinking to ensure the effectiveness and continuous improvement of Amtrak’s Revenue Management System (RMS). The Principal OR Scientist will serve as the analytical owner of RMS decision quality, responsible for defining and prototyping analytical approaches for forecasting, pricing, and optimization, rigorously evaluating system performance and outputs, translating business requirements into analytical frameworks and vendor deliverables, and partnering closely with Revenue Management users, Digital Technology teams, and external RMS vendors. While model implementation is primarily performed by vendor systems, this role requires deep expertise to guide, validate, and challenge model development, ensuring alignment with business objectives and measurable revenue impact. An ideal candidate is technically strong, intellectually curious, and comfortable operating at the intersection of analytics, systems, and product strategy.

Requirements

Bachelor’s Degree or equivalent combination of education, training and/or relevant experience.
Plus 7 years of relevant work experience.
Preferred Bachelor’s degree in Operations Research, Industrial Engineering, Computer Science, Statistics, Mathematics, or a related field
Preferred 7 years of experience in advanced analytical roles, ideally in revenue management, pricing, transportation, or related industries
Strong understanding of forecasting methods, optimization concepts, supply, demand and pricing dynamics
Advanced proficiency in SQL and experience working with large, complex datasets
Experience developing analytical prototypes and translating business problems into quantitative frameworks
Demonstrated experience evaluating model performance and defining success metrics for analytical systems
Strong communication skills, with the ability to translate complex analytical concepts for both technical and non-technical audiences
Ability to work independently and collaboratively in a dynamic, cross-functional environment
Requires an advanced analytical knowledge of data.
Ability to conduct large data analysis.
Ability to perform data conditioning for storage/moving capability.
Ability to program advanced computing.
Ability to develop algorithms, software and data models.
Ability to execute predictive analytics.

Nice To Haves

Bachelor’s Degree or equivalent combination of education, training and/or relevant experience. Plus 9 years of relevant work experience.
Master’s degree (or higher) in Operations Research, Industrial Engineering, Computer Science, Statistics, Mathematics, or a related field
Direct experience with Revenue Management Systems (RMS) in airline, rail, or hospitality industries
Familiarity with inventory control concepts (e.g., bid-price logic, demand segmentation) and network or multi-segment optimization problems
Experience working with external vendors on analytical or system implementations
Experience with experimental design (A/B testing), model validation and performance monitoring
Practical experience with Python/R for data analysis, prototyping, or modeling

Responsibilities

Collaborate with Digital Technology and vendor support teams to ensure system reliability, data integrity, and quality across integrations between RMS and commercial systems, including the Reservation System
Oversee batch processing, error resolution, and recurring RMS operational health checks
Conduct troubleshooting and root-cause analysis of system and data issues, partnering with vendor and internal teams
Test, validate, and document vendor product updates, version upgrades, and enhancements
Communicate system changes, risks, and operational impacts to business users
Perform regression testing as prescribed by Enterprise Release Management
Design and prototype analytical approaches to improve forecasting, pricing, and inventory optimization within RMS
Translate business problems into structured analytical frameworks and solution concepts
Partner with vendor teams to translate validated analytical approaches into production-ready models
Evaluate new ideas using data, develop prototypes/POCs, and generate insights to inform system enhancements
Collaborate with Business Planning to align RMS evolution with long-term strategic opportunities
Contribute to defining next-generation capabilities leveraging AI/ML and advanced analytics
Define and track key performance metrics for RMS models and decision making, including Forecast accuracy, Revenue performance, Load factor and demand realization, System utilization vs manual overrides
Develop frameworks to diagnose model performance issues, identify bias, drift, and inefficiencies in system outputs
Conduct post-implementation analysis of model changes and enhancements
Establish feedback loops between business users, system outputs, and vendor teams
Partner with vendors to validate and challenge model performance and assumptions, ensuring measurable improvements
Co-own the RMS roadmap and enhancement backlog, prioritizing system gaps, analytical opportunities, and user pain points
Influence vendor roadmap development and validate delivered capabilities against business expectations
Drive change management, including documentation of best practices and development of training materials
Support onboarding and training to improve system adoption and effective usage
Participate in ideation, scoping, and requirements definition for RMS-related initiatives and integrations
Translate business and analytical requirements into clear specifications for vendor and engineering teams
Develop and execute validation frameworks for new features, models, and system enhancements
Track project progress, risks, and mitigation strategies, providing concise updates to stakeholders
Ensure smooth transition of new capabilities into steady-state operations
Provide guidance to analysts and stakeholders on analytical approaches, interpretation of results, and decision-making
Establish best practices in analytical rigor, experimentation and data validation
Elevate the team’s capability in understanding and applying revenue management and decision science concepts