Senior Data Scientist - Machine Learning

About the company:

ResortPass is redefining what it means to be a hotel guest. We’re building a new category in hospitality: day access to luxury hotel experiences from breathtaking pools and private beaches to deluxe spas and wellness recharges so people can escape without an overnight stay.

Our marketplace now connects guests with 2,300+ partner hotels and resorts, including Ritz-Carlton, Four Seasons, Marriott Hilton, and more.  We’ve helped millions of people enjoy premium hospitality close to home, making rest more mindful, togetherness more meaningful, and escape more accessible.  The result: unforgettable experiences for guests and new revenue streams for partners.

Backed by some of the best consumer and growth investors, including CRV, Declaration, Brian Kelly (The Points Guy), WME, FJ Labs, and more, ResortPass is scaling a product people love and creating an entirely new way to experience hospitality.

 

As our first dedicated Senior Data Scientist - Machine Learning, you’ll own the end-to-end lifecycle of models powering key product features—search ranking, recommendations, personalization, and dynamic pricing. You’ll collaborate closely with engineers, and product managers to design, train, deploy, monitor, and optimize scalable ML systems in production.

 

This role will be in person at our energetic NYC headquarters. The base salary for this role will range from $160,000 - $200,000 per year, and will be eligible for equity, commensurate with experience.

 

• Build & Productionize Models
  • Develop ML algorithms for search ranking, content recommendation, personalized user experiences, and dynamic pricing
  • Implement scalable data pipelines and feature stores to support real-time inference
• Collaborate & Integrate
  • Partner with software engineers to deploy models via microservices and serverless architectures
  • Work with product teams to translate business goals into technical requirements
• Experimentation & Evaluation
  • Design and analyze A/B tests to validate model improvements
  • Instrument monitoring and alerting for model performance, data drift, and business impact
• Optimization & Scale
  • Profile and optimize model latency, throughput, and resource utilization
  • Leverage cloud and big-data tools for large-scale training and inference

• Experience & Technical Skills
  • 5+ years in ML engineering, data science, or related role at a high-growth tech company
  • Expert in Python and ML frameworks (scikit-learn, TensorFlow or PyTorch)
  • Hands-on experience with recommendation systems, search algorithms, personalization engines, or dynamic-pricing models
  • Proficient with SQL, data-processing frameworks (Spark, Beam), and cloud services (AWS SageMaker, GCP AI Platform)
• Analytical & Collaborative
  • Strong statistical foundations and practice designing robust experiments
  • Excellent communicator: distills complex technical work into clear insights for both technical and non-technical stakeholders
  • Proven track record of cross-functional collaboration and iterative delivery
• Culture & Values
  • You’re driven by impact, curiosity, and a genuine passion for both ML and hospitality
  • You care about code quality, reproducibility, and fostering an inclusive, supportive team environment
• Bonus points if you have:
  • Prior experience at a multi-sided marketplace, e-commerce, or hospitality tech
  • Familiarity with MLOps tools (Kubeflow, MLflow), feature-store platforms, or real-time inference frameworks
  • Background in algorithmic pricing, yield management, or revenue-management systems

• You're a good person. While building a startup is hard, being a good person is not. We are creating a culture of people with whom you would look forward to working. While we offer incredible experiences to our guests, it is just as important to us to foster an incredible culture for our employees
• We encourage candidates to apply even if they don’t have 100% of the below qualifications. We believe in a holistic approach when evaluating talent for our team and post new roles often, so even if this role isn’t quite right, we want to meet you!

Benefits