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At Evolve, we’re on a mission to make vacation rental easy for everyone. Our high-performing, customer-obsessed team runs on curiosity, communication, and accountability—working together to create exceptional experiences for our owners and guests. Whether solving big challenges, delivering outstanding results, or celebrating wins, we approach every day with purpose and passion. If you’re ready to join a mission-driven company where every teammate has the opportunity to thrive, Evolve might just be the place for you. Why this role Evolve's Data Product team builds data and machine-learning products that improve owner acquisition and retention, pricing, revenue performance, and how teams make decisions. We're hiring a hands-on Staff Data Scientist with applied ML engineering depth to lead the highest-impact work across that portfolio. You'll turn ambiguous opportunities into durable production systems: frame the problem and success measures, develop and validate models, build the pipelines and inference patterns needed to run them, integrate them into products or workflows, and measure adoption and business impact. You'll also contribute directly to our economic and pricing work, including forecasting, demand and price-elasticity estimation, causal measurement, and optimization. This is an individual-contributor role for someone who enjoys both modeling and systems work. You'll set technical direction and pragmatic engineering standards for a lean data science team, mentor other contributors, and partner closely with Product, Engineering, Data Engineering, Revenue Management, and business leaders. The exact mix of initiatives will shift with company priorities, but end-to-end ownership and measurable business use will remain constant. This role reports to the head of Data Product. What you'll do Lead the technical direction and hands-on delivery of one or two prioritized applied ML or data science initiatives at a time. Translate business opportunities into clear decision frameworks, technical approaches, success measures, and plans for adoption and impact evaluation. Build and operate ML systems end to end, including data and feature pipelines, training and evaluation, batch or online inference, deployment, monitoring, failure handling, and iteration. Contribute directly to forecasting, demand and price-elasticity estimation, causal measurement, and optimization work that supports pricing and revenue decisions. Design and analyze experiments and quasi-experiments to evaluate product, model, and policy changes. Establish reusable standards for testing, reproducibility, versioning, observability, documentation, and responsible model operation; review designs and code across the team. Partner with Product, Engineering, Data Engineering, Revenue Management, and other business owners to make technical tradeoffs and integrate models into products and operating workflows. Mentor data scientists, raise the team's technical judgment, and create leverage beyond your own projects while remaining hands-on. What makes you a great fit Typically 6+ years applying data science, statistics, econometrics, or machine learning to consequential business problems. Evidence of Staff-level scope: you have led ambiguous, cross-functional DS or ML work from idea through sustained production use, influenced technical direction beyond one project, and created leverage for other contributors. Strong Python and SQL skills, including the ability to write tested, maintainable production code and work effectively with large datasets. Experience owning production ML systems, including deployment or scoring, monitoring, failure handling, operational support, and iteration after launch. Strong applied-statistics and model-evaluation judgment, including experimentation or causal-inference fundamentals and the ability to contribute to economic or optimization work. Ability to connect technical decisions to business outcomes and communicate tradeoffs clearly to technical, product, business, and executive audiences. A self-directed, collaborative working style: you can prioritize across a broad problem space, receive and give direct feedback, influence without formal authority, and remain hands-on in a lean, remote team. Helpful experience An advanced degree in a quantitative field, or equivalent depth demonstrated through applied work. Demand forecasting, dynamic pricing, revenue management, price-elasticity estimation, econometrics, causal inference, or optimization. Snowflake, dbt, cloud orchestration, and practical MLOps or model-governance patterns. Marketplace, travel, hospitality, or another domain where models influence high-frequency operating decisions. NLP, LLM, voice, or other unstructured-data products. Compensation Annual base salary range: $180,000–$195,000, depending on relevant experience. This role is also eligible for equity and a variable annual bonus based on both company and individual performance. Location All Evolve team members must live in one of our approved locations by their first day. We can hire from anywhere in the U.S. except D.C. and Hawaii. Some positions may also have restrictions based on compensation in the following states: California, Maryland, New York, Pennsylvania, Rhode Island, and Washington. If you live in Colorado, you can work remotely anywhere in the state, at our downtown Denver office, or a hybrid of both! If you're planning to move soon, please let us know, and we'll be happy to review your application again. California Applicant Privacy Policy | Evolve How we reward Evolvers We’re intentional about offering benefits that empower every Evolver to thrive both professionally and personally because they’re more than perks—they’re investments in our customer-obsessed, high-performing team. We believe in treating others as they want to be treated, providing benefits that deliver real value, and challenging the status quo to meet the diverse needs of our team. Whether it’s helping you take care of your health, plan for the future, or celebrate life’s milestones, our offerings are designed to support you every step of the way. Financial Wellness: Industry-competitive pay, equity in the company, and a 401(k) with a 4% immediate vesting match. Family Support: 16-18 weeks of paid parental leave for birthing parents and 10 weeks for non-birthing parents, plus infertility coverage. Health & Wellness: Comprehensive medical, dental, and vision plans, with 100% employer-paid dental and vision for individual coverage, a low-cost medical option, 10 free mental health visits, and pet insurance. Time to Recharge: Generous PTO, RTO (for full-time exempt employees), sick leave, holidays, and a personal holiday to celebrate what matters most to you. Travel Perks: Annual Evolve travel credit after one year and discounts on stays at all Evolve properties. Growth Opportunities: World-class onboarding programs, learning, and development resources to help you grow your impact. Connection: Employee Resource Groups celebrating our diverse communities at Evolve. How we work together With our core values as our guide, every Evolver helps shape the company we want to work for and the people we want to be. We’ve cultivated a culture of collaboration, care, and responsibility that we can all be proud of, and we’re excited to see what you’ll bring as your authentic self. Still curious about who we are and what we do? Read more about our business and our culture at . EEO At Evolve, we are committed to diversity and inclusion. As an equal opportunity employer, all qualified candidates will be considered for employment without regard to race, color, creed, religion, age, sex or gender (including pregnancy, childbirth, lactation and related medical conditions), gender identity or gender expression, sexual orientation, marital status, national origin, ancestry, citizenship status, military service or veteran status, physical or mental disability, or any other legally protected characteristic. Evolve participates in e-Verify for all positions. If you have a disability or special need that requires accommodation at any point in the hiring process, please let your recruiter know. Originally posted on Himalayas