Lead Data Scientist at Apartment List
United States
$145k - $202k
<h2><strong style="color: rgb(123, 45, 139); background-color: transparent;">The Opportunity</strong></h2><div><br></div><div><span style="color: rgb(51, 51, 51); background-color: transparent;">Apartment List is looking for a Lead Data Scientist to build, deploy, and improve machine learning models that power our two-sided rental marketplace.</span></div><div><br></div><div><span style="color: rgb(51, 51, 51); background-color: transparent;">In this role, you’ll work on meaningful data science problems across demand- and supply-side modeling — from renter acquisition and intent signals to ranking, personalization, and marketplace optimization. You’ll take ownership of projects end-to-end, from problem framing through production launch and measurement, and collaborate closely with Product, Engineering, and Analytics along the way.</span></div><div><br></div><div><span style="color: rgb(51, 51, 51); background-color: transparent;">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 there’s still a tremendous amount of opportunity ahead. This is a role for someone who is ready to take on complex, well-scoped projects independently and grow into increasingly ambiguous, high-leverage work.</span></div><h2><br></h2><h2><strong style="color: rgb(123, 45, 139); background-color: transparent;">Here’s what you’ll do as part of the team</strong></h2><div><br></div><ul><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">Translate customer, marketplace, and business problems into clear ML objectives, features, models, and measurement plans.</span></li><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">Build, deploy, and iterate on production machine learning models across ranking, personalization, renter intent, demand-side acquisition, and supply-side optimization.</span></li><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">Own projects end-to-end — from feature engineering and model development through A/B experimentation, launch, and monitoring.</span></li><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">Apply a strong statistical mindset to model development, evaluation, causal inference, and tradeoff analysis.</span></li><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">Partner with Product, Engineering, and Analytics to align on success metrics, deployment plans, and downstream impact.</span></li><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">Communicate technical findings and model tradeoffs clearly to both technical and non-technical stakeholders.</span></li><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">Leverage AI tools to improve your productivity across coding, analysis, documentation, and workflow automation.</span></li></ul><h2><br></h2><h2><strong style="color: rgb(123, 45, 139); background-color: transparent;">Here are the skills and experience you’ll need to be successful</strong></h2><div><br></div><div><strong style="color: rgb(51, 51, 51); background-color: transparent;">Must-haves</strong></div><ul><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">4+ years of industry experience developing and deploying machine learning models in production, end-to-end.</span></li><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">A degree in Data Science, Computer Science, Computer Engineering, Mathematics, Statistics, Economics, Physics, or a related quantitative field.</span></li><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">Deep proficiency in Python and SQL, with comfort across the full model development lifecycle.</span></li><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">Familiarity with standard ML libraries and frameworks such as scikit-learn, XGBoost, TensorFlow, PyTorch, or similar.</span></li><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">Experience working with cloud platforms (GCP preferred but not required).</span></li><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">Strong grounding in statistical learning, experimental design, and model evaluation.</span></li><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">Ability to work through feature engineering, feature selection, hyperparameter tuning, and model optimization independently.</span></li><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">Comfort communicating and collaborating with cross-functional partners across Product, Engineering, and Analytics.</span></li></ul><div><br></div><div><strong style="color: rgb(51, 51, 51); background-color: transparent;">Nice-to-haves</strong></div><ul><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">Experience in a two-sided marketplace or multi-stakeholder environment.</span></li><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">Background in recommendation systems, ranking, personalization, or search.</span></li><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">Familiarity with MLOps practices, model monitoring, Airflow, dbt, or similar infrastructure.</span></li><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">Experience with performance marketing models, paid acquisition, or supply-side optimization.</span></li><li class=""><span style="color: rgb(51, 51, 51); background-color: transparent;">A master’s degree or higher in a relevant quantitative field.</span></li></ul><h2><br></h2><h2><strong style="color: rgb(0, 0, 0); background-color: transparent;">What’s in it for you</strong></h2><div><br></div><ul><li class=""><strong style="background-color: transparent;">Impact:</strong><span style="background-color: transparent;"> Work on ML systems that directly shape the renter experience, property partner outcomes, and company performance.</span></li><li class=""><strong style="background-color: transparent;">Ownership:</strong><span style="background-color: transparent;"> Build and own models end-to-end, from ambiguous opportunity through production launch and iteration.</span></li><li class=""><strong style="background-color: transparent;">Exceptional colleagues:</strong><span style="background-color: transparent;"> Our hiring bar is high, and your teammates are talented, motivated, collaborative, and intellectually curious.</span></li><li class=""><strong style="background-color: transparent;">Influence:</strong><span style="background-color: transparent;"> Have a strong voice within R&D and across the business, helping shape product, marketplace, and company strategy through data science.</span></li><li class=""><strong style="background-color: transparent;">A critical function:</strong><span style="background-color: transparent;"> Help build and scale one of the most important technical capabilities at Apartment List.</span></li><li class=""><strong style="background-color: transparent;">Culture:</strong><span style="background-color: transparent;"> Work in a virtual-first environment that allows you to work from anywhere in the U.S.</span></li></ul><div><br></div><div><strong>Here's the Pay Range:</strong></div><div><br></div><div>At Apartment List, we carefully consider a variety of factors to determine compensation for each position, including the role, level, and work. The US base salary range for this position is:</div><div><br></div><ul><li class="">Zone 1: $189,000 - $230,000 TTC (including $170,000 - $202,000 base salary) + equity</li><li class="">Zone 2: $175,000 - $212,000 TTC (including $158,000 - $186,000 base salary) + equity</li><li class="">Zone 3: $161,000 - $195,000 TTC (including $145,000 - $172,000 base salary) + equity</li></ul><div><br></div><div>This reflects the compensation target for new hire salaries for the position across all US locations. Please note, the compensation details provided do not include benefits and perks that we offer. </div><div><br></div><div>We also rely on market indicators along with considering your work location, job related skills, experience and relevant education and training, to determine compensation that is fair and competitive for you. Apartment List will consider paying compensation near the higher of the range in exceptional circumstances, where candidates have the experience, credentials or expertise that would warrant such consideration. It is always our goal to hire exceptional talent and we would be happy to share more about compensation during the hiring process.</div>
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