Lead Data Scientist

 Posted a day ago
     
 $161K - $230K per year
  
5-10 years experience
Apply Now

Please mention DailyRemote when applying

AI Summary

Build, deploy, and iterate on production machine learning models for ranking, personalization, and marketplace optimization. Own the end-to-end lifecycle from problem framing and feature engineering to A/B testing and production monitoring.

The Opportunity


Apartment List is looking for a Lead Data Scientist to build, deploy, and improve machine learning models that power our two-sided rental marketplace.

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.

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.


Here’s what you’ll do as part of the team


  • 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.


Here are the skills and experience you’ll need to be successful


Must-haves
  • 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.

Nice-to-haves
  • 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.


What’s in it for you


  • Impact: Work on ML systems that directly shape the renter experience, property partner outcomes, and company performance.
  • Ownership: Build and own models end-to-end, from ambiguous opportunity through production launch and iteration.
  • Exceptional colleagues: Our hiring bar is high, and your teammates are talented, motivated, collaborative, and intellectually curious.
  • Influence: Have a strong voice within R&D and across the business, helping shape product, marketplace, and company strategy through data science.
  • A critical function: Help build and scale one of the most important technical capabilities at Apartment List.
  • Culture: Work in a virtual-first environment that allows you to work from anywhere in the U.S.

Here's the Pay Range:

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:

  • Zone 1: $189,000 - $230,000 TTC (including $170,000 - $202,000 base salary) + equity
  • Zone 2: $175,000 - $212,000 TTC (including $158,000 - $186,000 base salary) + equity
  • Zone 3: $161,000 - $195,000 TTC (including $145,000 - $172,000 base salary) + equity

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. 

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.

Similar Jobs

See all Remote Software Development jobs →

Personalize your Remote Job Search in 3 Easy Steps!

Discover remote opportunities in Data Scientist

Answer easy questions

Answer easy questions

200,000+ jobs across 15+ categories

Get your best job matches

Get your best job matches

Only hand-screened, legit jobs

Find a remote job faster

Find a remote job faster

No ads, scams, or junk

I was the first applicant for a remote marketing position that got listed on the company website the same day I applied. Had an interview within 48 hours!

Sarah J. — Sarah J. · Marketing Manager ★★★★★ Verified