[Remote] Lead Data Scientist

Note: The job is a remote job and is open to candidates in USA. Apartment List is looking for a Lead Data Scientist to build, deploy, and improve machine learning models that power their two-sided rental marketplace. In this role, you will work on significant data science problems and take ownership of projects from problem framing through production launch and measurement, collaborating closely with Product, Engineering, and Analytics teams.

Responsibilities

• Translate customer, marketplace, and business problems into clear ML objectives, features, models, and measurement plans
• Build, deploy, and iterate on production machine learning models across ranking, personalization, renter intent, demand-side acquisition, and supply-side optimization
• Own projects end-to-end — from feature engineering and model development through A/B experimentation, launch, and monitoring
• Apply a strong statistical mindset to model development, evaluation, causal inference, and tradeoff analysis
• Partner with Product, Engineering, and Analytics to align on success metrics, deployment plans, and downstream impact
• Communicate technical findings and model tradeoffs clearly to both technical and non-technical stakeholders
• Leverage AI tools to improve your productivity across coding, analysis, documentation, and workflow automation

Skills

• 4+ years of industry experience developing and deploying machine learning models in production, end-to-end
• A degree in Data Science, Computer Science, Computer Engineering, Mathematics, Statistics, Economics, Physics, or a related quantitative field
• Deep proficiency in Python and SQL, with comfort across the full model development lifecycle
• Familiarity with standard ML libraries and frameworks such as scikit-learn, XGBoost, TensorFlow, PyTorch, or similar
• Experience working with cloud platforms (GCP preferred but not required)
• Strong grounding in statistical learning, experimental design, and model evaluation
• Ability to work through feature engineering, feature selection, hyperparameter tuning, and model optimization independently
• Comfort communicating and collaborating with cross-functional partners across Product, Engineering, and Analytics
• Experience in a two-sided marketplace or multi-stakeholder environment
• Background in recommendation systems, ranking, personalization, or search
• Familiarity with MLOps practices, model monitoring, Airflow, dbt, or similar infrastructure
• Experience with performance marketing models, paid acquisition, or supply-side optimization
• A master's degree or higher in a relevant quantitative field

Benefits

• Equity
• Work in a virtual-first environment that allows you to work from anywhere in the U.S.

Company Overview