# Staff Data Scientist

**Company:** [Apartment List](https://hotfix.jobs/companies/apartment-list)
**Location:** Remote
**Role:** Data Science
**Salary:** $196k – $280k/yr
**Experience:** 7+ years
**Skills:** Python, SQL, Machine Learning, Statistical Modeling, Causal Inference, experimental design, scikit-learn, xgboost, TensorFlow, PyTorch, GCP, feature engineering, hyperparameter tuning, Airflow, dbt
**Posted:** 2026-08-04

> Leads end-to-end machine learning work across renter acquisition, marketplace optimization, ranking, personalization, and matching. The role requires 7+ years of production ML experience, strong Python and SQL skills, statistical expertise, and cross-functional technical leadership.

## Job Description

## Responsibilities
- Understand customer, marketplace, and business problems through data and translate them into ML objectives, features, models, and measurement plans.
- Deliver and deploy end-to-end machine learning models, from problem framing and feature engineering through development, experimentation, launch, monitoring, and iteration.
- Build zero-to-one models and improve production models across demand, supply, ranking, personalization, renter intent, and marketplace optimization.
- Apply statistical methods to model development, experimentation, causal inference, tradeoff analysis, and decision-making.
- Lead ambiguous, high-leverage technical work by defining scope, evaluating approaches, managing tradeoffs, and aligning stakeholders.
- Partner with Product, Engineering, Design, Analytics, Marketing, GTM, and Growth.
- Communicate ML opportunities, tradeoffs, and results to technical and non-technical audiences, including senior stakeholders.
- Mentor and collaborate with data scientists.
- Leverage modern AI tools to improve coding, analysis, documentation, and workflow automation.

## Requirements
- 7+ years of industry experience, or equivalent experience, developing, deploying, and iterating on production machine learning models.
- Degree in Computer Science, Computer Engineering, Mathematics, Statistics, Economics, Physics, or a related quantitative field.
- Deep proficiency in Python and SQL across the model development lifecycle.
- Familiarity with standard ML libraries and frameworks such as scikit-learn, XGBoost, TensorFlow, PyTorch, or similar tools.
- Experience with cloud platforms; GCP experience is preferred but not required.
- Broad knowledge of statistical and machine learning methods.
- Strong grounding in statistical learning, modeling, experimental design and analysis, and causal inference.
- Experience with feature engineering, feature selection, hyperparameter tuning, model evaluation, and model optimization.
- Ability to research opportunities quantitatively, define technical strategy, set scope, manage timelines, and drive measurable outcomes.
- Strong cross-functional communication and collaboration skills.

## Nice-to-haves
- Experience optimizing 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, ML engineering workflows, model monitoring, Airflow, dbt, or similar infrastructure.
- Master’s degree or PhD in a relevant quantitative field.

## Compensation and Benefits
- Total compensation targets by US zone:
  - Zone 1: $231,000–$280,000, including $203,000–$238,000 base salary, plus equity.
  - Zone 2: $214,000–$259,000, including $188,000–$220,000 base salary, plus equity.
  - Zone 3: $196,000–$238,000, including $172,000–$202,000 base salary, plus equity.
- Medical, dental, and vision coverage with premiums covered for employees and dependents.
- Unlimited flexible time off, company holidays, recharge days, and a holiday break.
- Home office, health and wellness, parental and family leave, fertility, and family-forming reimbursements or benefits.
- 401(k) plan, team events, and company meetups.

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