About the role :

Top of Mind Labs builds and embeds senior technical talent into product teams at enterprise software companies and private-equity-backed businesses. This role places a Data Scientist inside the data science function of a US-based revenue management software company serving large travel and hospitality operators.

The mandate is execution in a live product environment, not prototyping. The team has a substantial backlog of validated improvement ideas - modernizing decade-old forecasting and pricing models, expanding optimization capabilities, and removing manual configuration - and needs a second pair of hands to run experiments, analyze results, and ship changes into production alongside the existing data science lead. Business context, priorities, and client-facing communication remain with the internal team; this role owns execution, testing, and analysis.

Responsibilities :

- Rebuild and extend the core price response model, currently based on legacy code and cascading segment-level fitting logic, and evaluate modern machine learning and deep learning alternatives.

- Build an analysis framework to characterize user overrides of model recommendations - distinguishing cases where sparse or unusual data justifies an override from cases where model quality is the root cause.

- Contribute to group pricing optimization work supporting an enterprise customer expansion, taking ownership of discrete facets of the optimization problem.

- Modernize legacy time series demand forecasting code, running new implementations in parallel against the production system on a subset of properties to validate accuracy parity or improvement and runtime gains without service disruption.

- Design and run back-tests and live parallel experiments, including the helper utilities and harnesses required to spin experiments up quickly.

- Define fitness metrics and evaluation criteria for experiments, including heuristic approaches for decisions that resist clean scoring, such as inventory optimization quality and specific pricing decisions.

- Replace manually set parameters and manual model selection with data-driven learning, reducing configuration burden and improving outcomes.

- Translate experiment results into clear written analysis that supports go/no-go decisions on production rollout.

Required qualifications :

- 4+ years building and deploying statistical or machine learning models in production, ideally in pricing, forecasting, revenue management, or a comparable quantitative domain.

- Strong applied time series forecasting background across classical and modern approaches - ARIMA/ARMA and state space methods, gradient boosting, and neural forecasting architectures.

- Practical experience with constrained optimization : formulating objective functions, encoding business constraints, and evaluating solution quality.

- Advanced Python, with production-grade code quality and comfort working inside an existing codebase rather than in notebooks alone.

- Demonstrated rigor in experimental design, back-testing methodology, and evaluation metric selection.

- Ability to work independently against a written backlog, with clear written communication of methods and findings to a distributed team.

Preferred qualifications :

- Experience in hospitality, airline, retail, or another dynamic pricing or revenue management context.

- Experience refactoring and modernizing legacy analytical code while preserving behavior.

- Familiarity with shadow deployment, champion/challenger testing, or other parallel-run validation patterns.

- Exposure to demand modeling, price elasticity estimation, or inventory control.

Working model :

The Data Scientist reports into Top of Mind Labs and works day-to-day alongside the client's data science lead, with senior oversight and hands-on technical direction provided by a Top of Mind Labs principal.