Data Scientist
About the job
- Have 0–2 years of experience in data science, analytics, machine learning, or a related field, including internships, research, senior projects, or meaningful independent projects.
- Hold a bachelor's or master's degree in statistics, mathematics, operations research, computer science, engineering, or another quantitative field.
- Have hands-on coding experience in Python, working knowledge of SQL, and familiarity with modern data analysis and machine learning workflows.
- Be able to structure ambiguous problems, choose sensible analytical approaches, and explain trade-offs, limitations, and recommendations clearly.
- Have an interest in hospitality, travel, pricing, forecasting, or other business problems where analytics can directly influence outcomes.
- Build machine learning and AI solutions that support pricing, forecasting, and revenue management decisions in hospitality.
- Analyze large, sometimes messy datasets to identify patterns, risks, and opportunities, and turn them into practical recommendations or product capability.
- Write clean Python and SQL, working with data pipelines and analytical workflows to prepare, validate, and operationalize data.
- Apply modern AI techniques, including large language models and AI coding tools such as Claude Code, thoughtfully to accelerate prototyping, learning, and development while maintaining technical quality.
- Partner closely with product, engineering, and cross-functional stakeholders to translate business problems into analytical solutions and communicate insights clearly.
- Have experience with revenue management, pricing, forecasting, segmentation, or related analytical problem spaces.
- Have experience building something reusable or scalable, such as a data pipeline, internal tool, model workflow, or decision-support analysis.
- Be familiar with cloud platforms, business intelligence tools, or modern AI tooling in technical workflows.
About the company
Revenue Analytics provides SaaS pricing and revenue management tools for industries such as hospitality, manufacturing, distribution, private equity, media, and passenger rail. The platform analyzes data and suggests pricing strategies to optimize revenue, with ongoing analytics services and support to help implement pricing decisions at scale. Customers subscribe to the platform, which integrates with their data, runs scenarios, and outputs actionable pricing guidance to maximize revenue. The company differentiates itself by serving a wide range of industries with tailored pricing solutions and combining software with analytics and ongoing support to deliver measurable results, aiming to improve profitability and forecasting through precise, scalable pricing.
Company Size
51-200
Company Stage
Series A
Total Funding
$11M
Headquarters
Atlanta, Georgia
Founded
2005
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Simplify's Take
What believers are saying
- 2026-06-24 IDC MarketScape named Revenue Analytics a Major Player in hospitality.
- 2026-08-05 Lead Edge Capital-backed growth support followed Climber's 2025 acquisition.
- 2026-03-17 RateGain partnership added fresher competitive-rate intelligence to N2Pricing.
What critics are saying
- 2026-09-01 Hotel Tech Report ranks RoomPriceGenie, Duetto, and IDeaS ahead of Revenue Analytics.
- 2026-07-15 BForest lists eleven B2B pricing vendors and ten hospitality RMS rivals.
- CMI depends on industrial adoption by 2027; one failed rollout damages the brand.
What makes Revenue Analytics unique
- 2026-06-16 CMI monitors industrial margin leakage across price, customer, product, cost, sales behavior.
- 2026-06-15 Climber RMS automates 24/7 hotel pricing for independents and regional chains.
- 2026-02-25 Cloudbeds and Revenue Analytics integrated Climber directly into PMS workflows.
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