Data Scientist, Marketing
Data Scientist, Marketing
Data Scientist, Marketing
Replit
Replit is seeking a Data Scientist for Marketing to leverage user behavior insights to enhance marketing strategies and drive revenue growth. The role involves designing marketing experiments, building predictive models, and creating dashboards to optimize campaigns across various channels. The ideal candidate will have a strong background in data science, particularly in marketing analytics, and proficiency in SQL and Python.
Qualification
- 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, statsmodels, etc.).
- Experience designing and analyzing A/B tests and experiments, including statistical rigor around sample sizing, significance testing, and causality.
Responsibility
- 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 product analytics.
