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.
Responsibilities
- Design and analyse marketing experiments to optimise 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, optimise 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.
- Analyse cohort behaviour and retention patterns to optimise lifecycle marketing campaigns and reduce churn.
- Develop segmentation models to personalise 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.
- 4+ years of experience in data science 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 behaviour data, and designing ETL workflows using dbt
- Proficiency in Python and data science libraries (pandas, scikit-learn, statsmodels, etc.).
- Experience designing and analysing A/B tests and experiments, including statistical rigor around sample sizing, significance testing, and causal inference.
- Experience building dashboards and visualisations (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, BigQuery, Snowflake, Fivetran, etc.).
- Background in growth analytics, marketing analytics, or conversion rate optimisation at a SaaS or PLG company.
- Familiarity with marketing technology platforms (Google Analytics, Segment, Iterable, Marketo, HubSpot, etc.).
- Experience with attribution modelling, marketing mix modelling, or incrementality testing.
- Understanding of PLG (product-led growth) motions and self-serve conversion funnels.
Bonus Points
- Experience analysing 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 analyse expansion revenue and upsell opportunities.
Full-Time Employee Benefits Include
- Competitive Salary & Equity
- 401(k) Program with a 4% match
- Health, Dental, Vision and Life Insurance
- Short Term and Long Term Disability
- Paid Parental, Medical, Caregiver Leave
- Commuter Benefits
- Monthly Wellness Stipend
- Autonomous Work Environment
- In Office Set-Up Reimbursement
- Flexible Time Off (FTO) + Holidays
- Quarterly Team Gatherings
- In Office Amenities
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