Principal Data Scientist at Hotel Engine

We are looking for a Principal Data Scientist to join our fast-growing Data Science and Engineering team and lead the work on key data and machine learning models and services. Establishing and maintaining high-quality data assets, data infrastructure, and data science capabilities is critical for the company's continued success. We have and will continue to invest heavily to leverage data science and machine learning to drive strategic and business decisions, power key product features, and solve problems that directly improve our customers’ experience and the strength of our business, including pricing, personalization and retention.
This is a key leadership role within the data team, with broad strategic and technical responsibilities, an opportunity to directly influence the direction of the product and the business, and significant growth potential. The individual must be highly motivated, a self-starter with a strong track record as an individual contributor in data science and/or machine learning, and both an obsession for rigorous work and bias for action.
You are not expected to be an expert in all the areas listed below. We are building a team focusing on people’s strengths, not lack of weaknesses. If you are passionate about data and machine learning systems, about travel, and relate to our vision and DNA, please apply.
Here's what you'll do:

Partner with stakeholders across Product, Engineering, Growth, Marketing, Finance, etc…\ to derive requirements, scope data services/systems and drive results
Lead end-to-end process including conception, development, production, deployment, and monitoring of data and machine learning models and services
Lead the team’s work on pricing, recommendation, lead scoring, retention
Lead product and growth experiments
Provide technical leadership to scientists/analysts working on data analytics projects and deliverables aiming at increasing growth/retention/profitability
Work closely with data and platform engineers to scale our data infrastructure in line with the needs of the business and of the data team (data acquisition, ETL pipelines, reporting infrastructure, feature stores, etc.)
Work closely with the VP, Data Science and the rest of the leadership team to define and deliver on the data science and engineering strategic roadmap and OKRs
Work with the VP, Data Science to build and coach a world-class team of data scientists, data engineers and machine learning engineers

Here's what we're looking for:

8+ years of industry experience as a data scientist / ML engineer in high-growth environments
Master's degree or PhD in Computer Science, Engineering, Economics, Statistics, or another quantitative discipline
Prior experience applying machine learning to real-world data problems (pricing, recommendation, personalization, etc.) and deploying and scaling models into a production environment
Track record of rigorous execution and high impact
Strong fundamentals in algorithms, statistics and predictive modeling
Excellent Python skills and experience with ML libraries or platforms
Demonstrable experience in system/software architecture and development
Ability to solve complex analytical problems using quantitative approaches with a unique blend of analytical, mathematical and technical skills
Excellent communication skills – can articulate goals/architecture/methodologies clearly and communicate insights in an easily accessible way to a diverse set of stakeholders
Highly detailed-oriented and exceptional organizational and follow-through skills is a must
Experience with AWS technologies is a plus

Cash compensation:

The base salary for this role starts at $150,000/year. Final offer amounts are determined by multiple factors, including prior experience, expertise & may vary from the amount above.

Remote Opportunities:

This role is eligible for remote work. Hotel Engine is authorized to do business in AZ, CA, CO, CT, FL, NC, NJ, NY, PA, TN, TX & WA. If you are not located in or able to work from a state where Hotel Engine is registered, you will not be eligible for employment. Please speak with your recruiter to learn more.