Staff Data Scientist

Who We Are At Apartment List, we’re transforming how people rent—making it smarter, easier, and a lot less frustrating. Our platform has already matched over 1.4 million renters with their next home, while helping properties fill units with the right residents. Backed by strong growth and a big vision, we’re building the future of renting—and inviting bold thinkers to help us shape it! The Opportunity Apartment List is looking for a Staff Data Scientist to help us attract and match the right renter with the right property at the right time. In this role, you’ll work on some of the most important data science problems across Apartment List — from demand-side renter acquisition and marketing models like User Value Modeling, to supply-side partner models like Supply Value Score, to ranking, personalization, renter intent, and emerging Pathmaker AI work that coordinates the renter journey in real time. Our Data Science team has a strong foundation. Over the last several years, we’ve delivered 40%+ incremental revenue growth through rigorously A/B tested machine learning models — and we’re still scratching the surface of what ML can do for renters, partners, and the business. You’ll build zero-to-one models in areas still powered by heuristics and business rules, while also improving existing production ML systems across ranking, personalization, renter intent, and marketplace [... source excerpt omitted ...] d partner deeply with Product, Engineering, Design, Analytics, Marketing, GTM and Growth to turn ambiguous opportunities into measurable impact. What you’ll do Deeply understand customer, marketplace, and business problems through the lens of data, and translate that understanding into clear ML objectives, features, models, and measurement plans. Deliver and deploy end-to-end machine learning models, from problem framing and feature engineering through model development, experimentation, launch, monitoring, and iteration. Build zero-to-one models in areas where heuristics or business rules are still in place, and improve existing production models across demand, supply, ranki [... source excerpt omitted ...] ntation, and workflow automation. What you’ll bring 7+ years of industry experience, or equivalent experience, developing, deploying, and iterating on machine learning models in production. A degree in Computer Science, Computer Engineering, Mathematics, Statistics, Economics, Physics, or a related quantitative field. Deep proficiency in Python and SQL, with comfort working across the full model development lifecycle. Familiarity with standard ML libraries and frameworks such as scikit-learn, XGBoost, TensorFlow, PyTorch, or similar tools. Experience working with cloud platforms; GCP experience is preferred but not required. Experience with a broad set of statistical and mac