Data Scientist: Growth Analytics & ML for Revenue

Success Booster; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Success Booster is seeking a senior data scientist to lead marketing and revenue modelling, including LTV, retention, and cohort analyses. You will partner with Paid Media, RevOps, Product Insights, and GMs to set KPIs and framework for launches and features, building scalable pipelines for ML workflows and real-time inference.

You will develop predictive models for conversion, churn, and engagement, identify prescriptive analytics opportunities, and translate insights into actionable business

Qualifications

• Bachelor's degree in a quantitative field.
• 5+ years in data science, growth analytics, or decision science roles.
• Strong SQL and Python skills (Pandas, Scikit-learn, NumPy).
• Hands‑on experience with Tableau, Looker, or similar BI tools.
• Familiarity with LTV modelling, retention curves, cohort analysis, and media attribution.

Responsibilities

• Own end-to-end modelling of LTV, user segmentation, retention, and marketing efficiency to inform media optimization and value attribution.
• Collaborate with Paid Media and RevOps to optimize SEM performance, predict high-value cohorts, and drive strategic bidding and targeting.
• Work closely with Product Insights and GMs to define core metrics, KPIs, and success frameworks for new launches and features.
• Conduct deep-dive analysis of user behaviour, funnel performance, and product engagement to uncover actionable insights.
• Monitor and explain changes in key product metrics, identifying root causes and business impact.
• Work with Data Engineering to design and maintain scalable data pipelines that support ML workflows, model retraining, and real-time inference.

Skills

SQL

Python

Communication

Data analysis

Education

Bachelor's degree in a quantitative field

Tools

Tableau

Looker

Pandas

Scikit-learn

NumPy

Job description

Success Booster is seeking a senior data scientist to lead marketing and revenue modelling, including LTV, retention, and cohort analyses. You will partner with Paid Media, RevOps, Product Insights, and GMs to set KPIs and framework for launches and features, building scalable pipelines for ML workflows and real-time inference.

You will develop predictive models for conversion, churn, and engagement, identify prescriptive analytics opportunities, and translate insights into actionable business