PRODUCT DATA SCIENTIST

It Face Inc.

San Francisco, CA, United States

9 days ago

Apply on www.dice.com

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

A/B Testing Artificial Intelligence Airflow R (Programming Language) Python (Programming Language) Machine Learning Scrum Methodology SQL Databases Usage Analysis Sql Optimization Large Language Models Generative AI

+1 more

Data Pipelines

Job description

We are looking for an experienced Product Data Scientist with strong Banking, FinTech, or Consumer Lending experience to work closely with Product Management and Engineering teams., * Partner with Product Managers to translate business questions into actionable insights

Design, execute, and interpret A/B tests and quasi-experiments
Develop product metrics, funnel definitions, cohort frameworks, and analytical methodologies
Collaborate with Engineering teams on event tracking, instrumentation, and data quality
Build SQL and dbt models and support data pipelines for product analytics
Develop, validate, and monitor statistical and machine learning models
Perform propensity, conversion, segmentation, risk, and pricing analytics
Monitor product and experiment performance and identify business opportunities
Present analytical findings, insights, and recommendations to Product teams and senior stakeholders
Leverage AI and LLM tools for exploratory analysis and documentation with appropriate validation

Requirements

5+ years of experience in Data Science, Product Analytics, Applied Statistics, or a related field
Strong Banking, FinTech, Consumer Lending, or Financial Services experience
Advanced SQL skills
Strong Python or R programming experience
Strong understanding of A/B testing, experimentation, and causal inference
Experience developing and applying statistical and machine learning models
Experience with product funnels, cohorts, metrics, and product analytics
Experience with dbt, data pipelines, or data modeling
Strong communication and stakeholder management skills
Experience partnering closely with Product Management and Engineering teams

NICE TO HAVE

Home improvement lending or contractor financing experience
Credit, risk, or pricing modeling experience
Experience with Segment, mParticle, Amplitude, or similar product analytics platforms
Airflow or other data orchestration tools
Agile/Scrum experience
Generative AI or LLM experience