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Data Scientist, Marketing

Job in Foster City, San Mateo County, California, 94420, USA
Listing for: Replit, Inc.
Full Time position
Listed on 2025-12-30
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager, Data Scientist, Data Mining
Job Description & How to Apply Below

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide and over 500,000 business users, Replit is democratizing software development by removing traditional barriers to application creation.

Replit is redefining how software is built, and who gets to build it. Our mission is to achieve Autonomy for All: making programming accessible, collaborative, and powered by AI. To realize this vision, we are building a brand that is as iconic, inventive, and human as the product itself.

You will directly impact Replit's growth by turning user behavior into actionable insights that optimize our marketing efforts, improve conversion funnels, and drive sustainable revenue growth across our self-serve and enterprise segments.

You will:
  • Design and analyze marketing experiments to optimize campaigns, messaging, and channel performance across email, paid ads, social, and content marketing.
  • Build attribution models and multi-touch conversion funnels to understand the customer journey from first touch to paid conversion.
  • Develop predictive models to identify high-intent prospects, optimize lead scoring, and improve targeting for paid acquisition campaigns.
  • Partner with marketing, growth, and revenue teams to translate business questions into rigorous analysis and clear recommendations.
  • Create self-service dashboards and automated reporting that surface key marketing metrics (CAC, LTV, ROAS, conversion rates) for go-to-market teams.
  • Build and maintain data pipelines that integrate marketing platforms (Google Ads, Meta, Iterable, Segment, etc.) with our product analytics.
Examples of what you could do:
  • Build propensity models to identify which free users are most likely to convert to plans based on usage patterns and engagement signals.
  • Analyze cohort behavior and retention patterns to optimize lifecycle marketing campaigns and reduce churn.
  • Develop segmentation models to personalize messaging and targeting for different user personas (students, hobbyists, professional developers, enterprise teams).
  • Build real-time alerting systems to flag anomalies in campaign performance or conversion metrics, automate bidding adjustments across platforms.
Required skills and experience:
  • Bachelor's degree in Computer Science, Statistics, Mathematics, Economics, or related field, OR equivalent real-world experience in data roles.
  • 2-4 years of experience in data science, analytics, or related roles with a focus on marketing, growth, or business analytics.
  • Strong SQL skills and experience working with large datasets, particularly event-level user behavior data, and designing ETL workflows using dbt
  • Proficiency in Python and data science libraries (pandas, scikit-learn, stats models, etc.).
  • Experience designing and analyzing A/B tests and experiments, including statistical rigor around sample sizing, significance testing, and causal inference.
  • Experience building dashboards and visualizations (Looker, Tableau, Mode, or similar tools).
  • Ability to translate ambiguous business questions into structured analysis and communicate findings clearly to non-technical stakeholders.
Preferred Qualifications:
  • Experience with modern data stack (dbt, Big Query, Snowflake, Fivetran, etc.).
  • Background in growth analytics, marketing analytics, or conversion rate optimization at a SaaS or PLG company.
  • Familiarity with marketing technology platforms (Google Analytics, Segment, Iterable, Marketo, Hub Spot, etc.).
  • Experience with attribution modeling, marketing mix modeling, or incrementality testing.
  • Understanding of PLG (product-led growth) motions and self-serve conversion funnels.
Bonus Points:
  • 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).
  • Familiarity with customer data platforms (CDPs) and event tracking implementation.
  • Experience working with sales and customer success data to analyze expansion revenue and upsell opportunities.

This is a full-time role that can be held…

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