TakeUp, LLC is revolutionizing revenue optimization for hospitality with a daring approach to pricing. Using AI and machine learning, TakeUp empowers independent operators to unlock maximum revenue potential through pricing courageously—day in, day out. Seamlessly integrated with top Property Management Systems, our platform replaces traditional rate-setting constraints with data-driven confidence, delivering an impressive 10-15x ROI.
Requirements
- Proficiency in Python (scikit-learn, XGBoost/LightGBM/CatBoost).
- Strong SQL skills and comfort with large, imperfect, real-world datasets.
- Experience across the full model lifecycle: data preparation, feature engineering, training, evaluation, deployment, and monitoring.
- Familiarity with experimentation design and metrics; able to reason about trade-offs and safeguards.
- Experience with causal inference (uplift modeling, causal forests, DML) or time-series modeling.
- Exposure to reinforcement learning concepts (multi-armed bandits, dynamic programming, temporal-difference learning).
- Experience with cloud data warehouses (Snowflake, BigQuery, Redshift) and dbt.
Responsibilities
- Design, train, and deploy production ML models, with emphasis on tree-based methods (XGBoost, LightGBM, CatBoost).
- Contribute to feature engineering and model evaluation approaches that balance accuracy, interpretability, and speed.
- Translate customer needs and product requirements into practical modeling tasks (classification, regression, ranking, uplift).
- Develop custom performance metrics to evaluate models’ ability to generate reasonable counterfactual demand estimates while accounting for varying customer product expectations.
- Support explainability efforts to justify rate decisions with clear artifacts and documentation.
- Build and maintain training and evaluation pipelines, ensuring offline metrics align with online business outcomes.
- Partner with engineering to integrate models into production services and batch jobs with defined SLAs.
Other
- 4+ years of experience building and deploying ML models to production.
- Clear communicator, comfortable working in a collaborative, fast-paced environment.
- Travel may be needed for customer discovery, team building, and/or networking.
- Former start-up experience.
