Data Scientist

Revenue Analytics·Remote(United States)
Data & Analytics

WFA Digital Insight

The demand for skilled data scientists in the digital marketing space has surged, with a notable 25% increase in job postings over the last year. As companies seek to make data-driven decisions, professionals with expertise in machine learning, AI, and analytics are in high demand. Revenue Analytics stands out for its innovative approach to revenue management, combining deep pricing expertise with modern software. Candidates should be prepared to showcase their ability to structure complex problems, choose sensible analytical approaches, and communicate insights clearly. Before applying, it's essential to understand the company's growth-stage mindset and the unique challenges of the hospitality industry.

Job Description

About the Role

As a Data Scientist at Revenue Analytics, you'll be part of a growth-stage company that's investing heavily in the future of hospitality revenue management. Your primary focus will be on building machine learning and AI systems that power the company's hospitality analytics platform. You'll work closely with cross-functional teams, including product, science, and engineering, to turn ambiguous questions into rigorous analytical solutions. This role is perfect for those who are excited about the opportunity to help build real product capability and drive measurable revenue uplift.

The hospitality industry presents a complex and fast-moving domain, with unique challenges in pricing, demand, and competitive analysis. As a Data Scientist, you'll need to be able to analyze large datasets, identify patterns, risks, and opportunities, and turn them into practical recommendations or product capabilities. Your work will directly influence product direction, enabling hospitality customers to make better, faster, and more data-driven decisions.

What You Will Do

  • Build machine learning and AI solutions that support pricing, forecasting, and revenue management decisions in hospitality
  • Analyze large datasets to identify patterns, risks, and opportunities, and turn them into practical recommendations or product capabilities
  • Write clean Python and SQL code, working with data pipelines and analytical workflows to prepare, validate, and operationalize data
  • Apply modern AI techniques, including LLMs and AI coding tools, to accelerate prototyping, learning, and development while maintaining technical quality
  • Partner with product, engineering, and cross-functional stakeholders to translate business problems into analytical solutions and communicate insights clearly
  • Develop and maintain technical documentation for data pipelines, models, and analytical workflows
  • Collaborate with the science team to design and implement experiments, and analyze results to inform product decisions
  • Work with the engineering team to integrate machine learning models into the product platform
  • Stay up-to-date with industry trends and emerging technologies in machine learning and AI

What We Are Looking For

  • 0-2 years of experience in data science, analytics, machine learning, or a related field, including internships, research, senior projects, or meaningful independent projects
  • Bachelor's or Master's degree in statistics, mathematics, operations research, computer science, engineering, or another quantitative field
  • Hands-on coding experience in Python, working knowledge of SQL, and familiarity with modern data analysis and machine learning workflows
  • Ability to structure ambiguous problems, choose sensible analytical approaches, and explain trade-offs, limitations, and recommendations clearly
  • Strong curiosity, ownership, and learning agility, with interest in hospitality, travel, pricing, forecasting, or other business problems where analytics can directly influence outcomes
  • Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams
  • Familiarity with cloud platforms, business intelligence tools, or modern AI tooling in technical workflows

Nice to Have

  • Experience with revenue management, pricing, forecasting, segmentation, or related analytical problem spaces
  • Experience building something reusable or scalable, such as a data pipeline, internal tool, model workflow, or decision-support analysis
  • Familiarity with modern AI techniques, including LLMs and AI coding tools
  • Knowledge of hospitality industry trends and challenges

Benefits and Perks

  • Opportunity to work with a growth-stage company that's investing heavily in the future of hospitality revenue management
  • Collaborative and dynamic work environment with a team of experienced professionals
  • Flexible remote work arrangements, with the option to work from anywhere in the United States
  • Access to cutting-edge tools and technologies, including machine learning and AI platforms
  • Professional development opportunities, including training and education programs
  • Competitive compensation package, with a focus on rewarding high-performance employees
  • Comprehensive benefits package, including health insurance, retirement planning, and paid time off

How to Stand Out

  • Develop a strong portfolio that showcases your ability to analyze complex datasets and communicate insights effectively.
  • Familiarize yourself with modern AI techniques, including LLMs and AI coding tools, to accelerate your workflow and improve technical quality.
  • Practice explaining technical concepts to non-technical stakeholders, as this is a key aspect of the Data Scientist role at Revenue Analytics.
  • Be prepared to discuss your experience with machine learning and AI, and how you've applied these technologies to drive business outcomes.
  • Research the hospitality industry and the challenges of revenue management, to demonstrate your interest and understanding of the domain.
  • Highlight your ability to work collaboratively with cross-functional teams, and your experience with agile development methodologies.
  • Prepare to back up your claims with specific examples, and be ready to walk the interviewer through your thought process and analytical approach.

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