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About the Role

Findigs runs an AI underwriting engine (DecisionAssist) that makes or influences thousands of rental decisions every week. As a Data Scientist, you will strengthen our data science and applied machine learning depth by owning hands-on model development, experimentation design, and ML-adjacent analysis that directly impacts renter and property manager outcomes. This is a highly technical, high-ownership role for a data scientist who wants to build and improve production models, bring statistical rigor to product decisions, and grow into broader strategic scope.

Responsibilities

• Own feature engineering, model iteration, and evaluation for DecisionAssist.
• Work across operational model work in the DA/CAV1 serving layer.
• Conduct analytics-focused modeling in Snowflake for experimentation and research.
• Partner with Product and Engineering on identifying relevant signals.
• Design and analyze experiments across underwriting, renter-facing, and PMC-facing product changes.
• Build and maintain models used in screening logic (e.g., delinquency risk, income estimation, fraud signals).
• Write clean Python, work in dbt, and operate in a modern data stack.
• Tackle high-impact, ad-hoc questions from Product and Customer teams regarding variance drivers, cohort behavior, and signal prediction.

Requirements

• 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).
• 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.
• Intellectual curiosity about housing and credit data.

Skills

• Python
• pandas
• scikit-learn
• statsmodels
• SQL
• dbt
• Snowflake
• Sigma
• Supervised Learning
• Classification
• Regression
• Tree-based methods
• A/B testing
• LLM experience (fine-tuning, retrieval, or integration)

Location

• NoHo office

Work Type

• Hybrid (3-4x times in-office per week)
• Full-time

Experience Level

• 4+ years of hands-on data science or applied ML experience

Salary/Compensations

• $160,000 - $185,000 a year

Benefits

• Pre-IPO equity
• Unlimited Paid Time Off (PTO)
• All-company holidays
• Health benefits
• 401(k) matching up to 4%
• Monthly gym stipend
• Lunch provided every day

About the Company

• Findigs is on a mission to make renting work for all of us by building the first end-to-end platform that turns complex screening into a seamless, high-trust experience for both property managers and renters.
• Fueled by $78M in funding from investors behind companies like Affirm, Gusto, and Uber.
• Aims to modernize one of the most essential industries.

Equal Opportunity

• As an equal opportunity employer, all applicants will be considered based solely upon merit and directly relevant professional competencies.