# Data Scientist, Marketing

**Company**: Replit
**Location**: Foster City, CA
**Work arrangement**: hybrid
**Experience**: mid
**Job type**: full-time
**Salary**: $180K - $250K
**Category**: Engineering
**Industry**: Technology
**Wikidata**: https://www.wikidata.org/wiki/Q60768699

**Apply**: https://jobs.ashbyhq.com/replit/c05749db-f413-4091-a95c-c8e0aa1b5630
**Canonical**: https://yubhub.co/jobs/job_fb622500-15e

## Description

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

## Skills

### Required
- SQL
- Python
- data science libraries (pandas, scikit-learn, statsmodels, etc.)
- ETL workflows using dbt
- A/B tests and experiments
- dashboard and visualisation tools (Looker, Tableau, Mode, etc.)

### Nice to have
- modern data stack (dbt, BigQuery, Snowflake, Fivetran, etc.)
- growth analytics, marketing analytics, or conversion rate optimisation
- marketing technology platforms (Google Analytics, Segment, Iterable, etc.)
- attribution modelling, marketing mix modelling, or incrementality testing