Data Scientist — Production ML & Experimentation (Equity)

Findigs, Inc.; New York (NY); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Hybrid schedule

Equity compensation

Unlimited PTO

Health benefits

401(k) matching

Job summary

Findigs is hiring a Data Scientist in NYC to strengthen our data science depth and production models. You will own hands-on model development, experimentation, and ML-adjacent analysis that directly impacts renter and property manager outcomes.

Reporting to the Lead Analytics Engineer, this highly technical role partners with Product and Engineering to translate real-world risk and behavior into actionable models, experiments, and insights. Hybrid in-office schedule in NoHo.

Qualifications

• 4+ years of hands-on data science or applied ML experience in fintech/proptech or similar high-stakes environments.
• Strong Python skills (pandas, scikit-learn, statsmodels or equivalent).
• Ability to design, run, and interpret A/B tests independently.
• Strong SQL skills and experience with a modern data stack (dbt, Snowflake, Sigma).
• Solid grounding in supervised learning (classification, regression, tree-based methods).
• Clear written communication to explain model behavior to non-technical partners.
• Curiosity about housing and credit data.

Responsibilities

• DecisionAssist model development: feature engineering, iteration, and evaluation.
• Experimentation and A/B testing across underwriting and product changes with rigorous analysis.
• Predictive and risk modeling for screening logic (delinquency risk, income estimation, fraud signals).
• ML infrastructure: writing clean Python, working in dbt, and operating in a modern data stack.
• Research and analysis for ad-hoc questions from Product and Customer teams.

Skills

Hands-on data science

Python

A/B testing

SQL

Supervised learning

Communication

Housing/credit data curiosity

Tools

dbt

Snowflake

Sigma

Job description

Findigs is hiring a Data Scientist in NYC to strengthen our data science depth and production models. You will own hands-on model development, experimentation, and ML-adjacent analysis that directly impacts renter and property manager outcomes.

Reporting to the Lead Analytics Engineer, this highly technical role partners with Product and Engineering to translate real-world risk and behavior into actionable models, experiments, and insights. Hybrid in-office schedule in NoHo.