Rocket Travel, Inc., a subsidiary of Booking Holdings, is seeking a skilled Data Scientist, Analytics to join our Data Science Team. Booking Holdings is the world's largest online travel conglomerate that includes Booking.com, Priceline, Kayak, Agoda, and other leading travel brands. Our mission is to help customers vacation faster by allowing customers to book hotels and earn thousands of airline miles. As an online travel agency (OTA), we operate our namesake rocketmiles.com, as well as white-label hotel booking portals for Southwest Airlines, Alaska Airlines, and other airline and non-airline partners.
Our data science team comprises seven data professionals - a mix of data scientists, analysts, and engineers - based entirely in our NYC office in the iconic Empire State Building. We are a centralized team that tackles a broad range of projects, from developing machine learning models, building data pipelines and BI dashboards, to performing ad-hoc "big data" analysis to derive insights and drive business decisions.
We are looking to add a data scientist to our team to scale our analytics capabilities. You will have the opportunity to collaborate with stakeholders across different products and functions, supporting and influencing them in both high-level strategic and tactical decisions. Examples of projects you might work on:
- Work with product teams to understand funnel conversion and suggest ideas for improvement
- Assist product owners to interpret and investigate counterintuitive A/B test results
- Analyze terabytes of auction data using Python, SQL, and Spark to benchmark supplier price competitiveness
- Build anomaly detection systems to identify anomalous changes in our hotel supply inventory
- Collaborate with marketing teams to improve attribution models and measure incremental lifts
- Evaluate and prototype Bayesian alternatives to measuring statistical significance of A/B tests
- Model customer lifetime value and assist Partnership, Marketing, and Customer Loyalty teams with their use cases
- 2+ years of industry experience in a quantitative role, preferably as a data scientist or data analyst. Candidates from other analytical backgrounds (e.g. management consulting, finance) also welcome if you can demonstrate required technical proficiency.
- Bachelor's degree in a quantitative discipline (e.g. statistics, mathematics, economics).
- Proficiency in Python & SQL. Familiarity with PySpark & AWS advantageous but not required.
- Practical knowledge of statistics (e.g. hypothesis testing, experiment design, sampling).
- Strong analytical intuition and business acumen.
- Excellent written and verbal communication skills. Capable of explaining technical concepts to non-technical audiences with ease.
- Intellectually curious and self-directed problem solver, keen to work on a variety of data problems.
- Having ownership in our products and our customers' experiences, building features that can be implemented and deployed in a matter of hours.
- Learning and growing professionally while being set up for success, collaborating closely with experienced business/design/technology teammates.
- Working with intrinsically motivated folks with a track record of delivering great products.
- Developing software using AWS, GitHub, modern development practices, and the best tools available.
- Receiving a competitive compensation package, including bonus, health/dental insurance, and 401k matching.
- Choosing your own computer/gear.
- Receiving a monthly cell phone stipend.
- Enjoying unlimited vacation, with free travel credits.
- Flexible teams that allow you to work remotely for those days when life needs you elsewhere.
- Learning at bi-monthly engineering lunch-and-learns for professional development.
- Enjoying free snacks, drinks, and coffee at our dog-friendly Chicago office in the West Loop.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
No recruiters, please.