# Staff Data Scientist

**Company:** [Apartment List](https://hotfix.jobs/companies/apartment-list)
**Location:** Remote
**Role:** Data Science
**Salary:** $172K-$238K
**Experience:** 7+ years
**Skills:** Python, SQL, scikit-learn, Xgboost, TensorFlow, PyTorch, GCP, MLOps, Airflow, dbt
**Posted:** 2026-05-08

> Staff Data Scientist builds and deploys end-to-end ML models for renter acquisition, personalization, ranking, and marketplace optimization in a two-sided rental platform. Requires 7+ years experience, Python/SQL proficiency, and strong statistical/ML skills.

## Job Description

## Responsibilities
- Deeply understand customer, marketplace, and business problems through data and translate into 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 powered by heuristics or business rules, and improve existing production models across demand, supply, ranking, personalization, renter intent, and marketplace optimization.
- Apply 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.
- Partner closely with Product, Engineering, Design, Analytics, Marketing, GTM and Growth to build ML systems that drive value.
- Communicate ML opportunities, tradeoffs, and results to technical and non-technical audiences.
- Mentor and collaborate with other data scientists to raise modeling, experimentation, and analytical practice.
- Leverage modern AI tools to improve productivity across coding, analysis, documentation, and workflow automation.

## Requirements
- 7+ years of industry experience developing, deploying, and iterating on machine learning models in production.
- Degree in Computer Science, Computer Engineering, Mathematics, Statistics, Economics, Physics, or related quantitative field.
- Deep proficiency in **Python** and **SQL**, comfort with full model development lifecycle.
- Familiarity with standard ML libraries and frameworks such as **scikit-learn**, **XGBoost**, **TensorFlow**, **PyTorch**, or similar.
- Experience with cloud platforms; **GCP** preferred.
- Broad set of statistical and machine learning methods to solve business problems.
- Strong grounding in statistical learning, modeling, experimental design and analysis, and causal inference.
- Ability to work through feature engineering, feature selection, hyperparameter tuning, model evaluation, and optimization.
- Ability to quantitatively research opportunities, define technical strategy, set scope, manage timelines, and drive outcomes.
- Comfort communicating and collaborating cross-functionally.

## Nice-to-Haves
- Experience optimizing within a two-sided marketplace or 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.
- Master's degree or PhD in relevant quantitative field.

## Compensation
- US base salary range: Zone 1: $203,000 - $238,000; Zone 2: $188,000 - $220,000; Zone 3: $172,000 - $202,000 + equity.

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