Data Scientist

Replit Replit · Enterprise · Foster City, CA · Hybrid · Engineering

Data Scientist role focused on building analytics and intelligence layers using AI and LLMs to understand customer behavior, optimize marketing, and automate insights delivery. The role involves designing experiments, building attribution models, synthesizing customer signals, and creating automated reporting, with a strong emphasis on using LLMs and agentic workflows for analysis.

What you'd actually do

  1. Synthesize customer signals — support tickets, social, reviews, CSAT — into automated intelligence that reaches the teams who need it
  2. Use LLMs and agentic workflows to analyze unstructured data at scale and automate recurring analysis
  3. Create automated reporting that put key metrics to inform the company
  4. Build churn and retention models to identify at-risk users and inform lifecycle intervention strategies
  5. Define and maintain customer segmentations and personas that drive targeting, messaging, and product decisions

Skills

Required

  • 6+ years of experience in data science with a focus on marketing, growth, or customer analytics
  • Strong SQL skills and experience with large-scale event-level user behavior data; experience designing ETL workflows using dbt
  • Proficiency in Python and data science libraries (pandas, scikit-learn, statsmodels, etc.)
  • Experience designing and analyzing A/B tests with statistical rigor (sample sizing, significance testing, causal inference)
  • Experience building dashboards and visualizations (Hex, Looker, Tableau, Mode, or similar) —> ideally automating them.
  • Demonstrated experience using LLMs/AI tools in analytics workflows — not just prompting, but building automated systems
  • Track record of partnering cross-functionally with Marketing, Product, Engineering, Support, and Revenue/Sales teams — not just serving a single stakeholder

Nice to have

  • Experience with modern data stack (dbt, BigQuery, Snowflake, Fivetran, Segment, etc.)
  • Background in growth analytics, marketing analytics, or conversion rate optimization at a SaaS or PLG company
  • Experience with marketing technology platforms (Google Analytics, Segment, Iterable, Salesforde)
  • Experience with attribution modeling, marketing mix modeling, or incrementality testing
  • Experience analyzing unstructured customer data (support tickets, reviews, social mentions) using NLP or LLM-based approaches
  • Understanding of PLG motions and self-serve conversion funnels
  • Experience with support analytics, CSAT analysis, or customer experience measurement
  • Experience analyzing freemium or usage-based pricing models
  • Understanding of developer tools, collaborative coding environments, or technical products
  • Experience with causal inference methods (difference-in-differences, synthetic control, propensity score matching)
  • Experience building AI agents or automated analytical pipelines using LLM APIs

What the JD emphasized

  • building automated systems

Other signals

  • Build agents and automated systems that deliver insights directly to the teams that need them
  • Use LLMs and agentic workflows to analyze unstructured data at scale and automate recurring analysis
  • Demonstrated experience using LLMs/AI tools in analytics workflows — not just prompting, but building automated systems