Staff Data Scientist

About the role

The Opportunity at Apartment List is seeking a Staff Data Scientist to join our dynamic team. You will play a pivotal role in driving innovation and growth through advanced data science techniques, focusing on areas such as demand-side renter acquisition, supply-side partner models, ranking, personalization, renter intent, and emerging Pathmaker AI work.

Responsibilities

• 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, ranking, personalization, renter intent, and marketplace optimization.
• Apply a strong statistical mindset to model development, experimentation, causal inference, tradeoff analysis, and decision-making.
• Lead ambiguous, high-leverage technical work: define scope, evaluate approaches, manage tradeoffs, and align stakeholders around a clear path forward.
• Partner closely with Product, Engineering, Design, Analytics, Marketing, GTM and Growth to build ML systems that drive renter value, property partner success, and business performance.
• Communicate ML opportunities, tradeoffs, and results clearly to technical and non-technical audiences, including senior stakeholders.
• Mentor and collaborate with other data scientists, helping raise the quality of our modeling, experimentation, and analytical practice.
• Thoughtfully leverage modern AI tools to improve productivity across coding, analysis, documentation, and workflow automation.

Requirements

• 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 machine learning methods to solve and optimize critical business problems and metrics.
• Strong technical and theoretical grounding in statistical learning, modeling, experimental design and analysis, and causal inference.
• Strong ability to work through feature engineering, feature selection, hyperparameter tuning, model evaluation, and model optimization.
• Ability to quantitatively research opportunities, define technical strategy, set clear scope, manage timelines, and drive measurable outcomes.
• Comfort communicating and collaborating with cross-functional audiences across Product, Engineering, Design, Analytics, Marketing, GTM and Growth and senior business stakeholders.
• Curiosity, judgment, and a hunger to dig into uncharted territory and make a meaningful impact.

Qualifications

• Experience optimizing within a two-sided marketplace or similarly complex multi-stakeholder environment.
• Background in recommendation systems, ranking, personalization, search, or matching.
• Experience with performance marketing models, paid acquisition, supply-side optimization, or marketplace incentives.
• Familiarity with MLOps practices, ML engineering workflows, model monitoring, Airflow, dbt, or similar infrastructure.
• A master’s degree or PhD in a relevant quantitative field.

Skills

• Python
• SQL
• Machine Learning Libraries (scikit-learn, XGBoost, TensorFlow, PyTorch)
• Cloud Platforms (GCP preferred)
• Statistical Learning, Modeling, Experimental Design, Causal Inference
• Feature Engineering, Feature Selection, Hyperparameter Tuning, Model Evaluation, Model Optimization
• Collaboration and Communication
• Modern AI Tools (e.g., MLOps, ML Engineering Workflows)

Benefits

Our benefits package includes:

• Flexible Work Arrangements
• Health Insurance
• Retirement Savings Plans
• Employee Assistance Programs
• Professional Development Opportunities

Pay

The US base salary range for this position is:

• Zone 1: $231,000 - $280,000 TTC (including $203,000 - $238,000 base salary) + equity
• Zone 2: $214,000 - $259,000 TTC (including $188,000 - $220,000 base salary) + equity
• Zone 3: $196,000 - $238,000 TTC (including $172,000 - $202,000 base salary) + equity