Data Scientist

Findigs, Inc.

Data Scientist enhancing AI underwriting with DecisionAssist for rental decisions. Collaborating with Product and Engineering to develop predictive models and analyses.

Posted 6/18/2026full-timeNew York City • New York • 🇺🇸 United StatesMid-LevelSenior💰 $160,000 - $185,000 per yearWebsite

Tech Stack

Tools & technologies

PandasPythonScikit-LearnSQL

About the role

Key responsibilities & impact

DecisionAssist model development: Own feature engineering, model iteration, and evaluation for DecisionAssist. You will work across two surfaces: (1) operational model work in the DA/CAV1 serving layer, and (2) analytics-focused modeling in Snowflake for experimentation and research, as well as partner with Product and Engineering on what signals matter and why.
Experimentation and A/B testing: Design and analyze experiments across underwriting, renter-facing, and PMC-facing product changes, and bring statistical rigor and clear recommendations.
Predictive and risk modeling: Build and maintain models used in screening logic (e.g., delinquency risk, income estimation, fraud signals).
ML infrastructure: While you won’t own the warehouse or pipeline architecture, you should be comfortable writing clean Python, working in dbt, and operating in a modern data stack.
Research and analysis: Tackle high-impact, ad-hoc questions from Product and Customer teams; e.g., what’s driving approval-rate variance, which cohorts behave differently, and what a given signal actually predicts.

Requirements

What you’ll need

4+ years of hands-on data science or applied ML experience (fintech, proptech, or other high-stakes decisioning environments preferred)
Strong Python skills (pandas, scikit-learn, statsmodels or equivalent); this is a coding role
Ability to design, run, and interpret A/B tests independently
Strong SQL skills and comfort working in a modern data stack (dbt, Snowflake, Sigma, or similar)
Solid grounding in supervised learning fundamentals (classification, regression, tree-based methods)
Strong written communication and the ability to explain model behavior and tradeoffs to non-technical partners (e.g., PMs, CSMs)
Intellectual curiosity about housing and credit data in particular

Benefits

Comp & perks

Location: We operate on a hybrid schedule (3-4x times in-office per week), with core collaboration days on Monday, Tuesday, and Thursday at our NoHo office.
Mission-Driven Culture: A collaborative, high-impact workplace where we challenge each other to grow, innovate, and drive meaningful change.
Competitive Compensation: Competitive base salary + Pre-IPO equity.
Generous Time Off: We trust our team to manage their own time and workload. That's why we offer a Unlimited Paid Time Off (PTO) policy, allowing you to take the time you need to rest and recharge. We also observe all-company holidays.
Wellness Perks: Health benefits, 401(k) matching up to 4%, monthly gym stipend, and lunch provided every day.

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Hard Skills & Tools

Pythonpandasscikit-learnstatsmodelsSQLsupervised learningclassificationregressiontree-based methodsA/B testing

Soft Skills

strong written communicationexplain model behaviorintellectual curiosity