Role & responsibilities

Marketing & Revenue Modelling
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 power strategic bidding and targeting.

Product & Growth Analytics
Work closely with Product Insights and General Managers (GMs) to define core metrics,

KPIs, and success frameworks for recent 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 closely with Data Engineering to design and maintain scalable data pipelines that

support machine learning workflows, model retraining, and real-time inference.

Predictive Modelling & Machine Learning
Build predictive models for conversion, churn, revenue, and engagement using

regression, classification, or time-series approaches.
Identify opportunities for prescriptive analytics and automation in key product and

marketing workflows.
Support development of reusable ML pipelines for production-scale use cases in

product recommendation,



lead scoring, and SEM planning.

Collaboration & Communication
Present insights and recommendations to a variety of stakeholders from ICs to

executives in a clear and compelling manner.
Translate business needs into data problems, and complex findings

Preferred candidate profile

What Youll Bring

Minimum Qualifications
Bachelors degree in a quantitative field (Mathematics, Statistics, CS, Engineering, etc.).
5+ years in data science, growth analytics, or decision science roles.
Solid 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.
Experience with GA4, Google Ads, Meta, or other performance marketing platforms.
Explicit communication skills and a track record of turning data into decisions.

Nice to Have
Experience with BigQuery and Google Cloud Platform (or equivalent).
Familiarity with affiliate or lead-gen business models.
Exposure to NLP, LLMs, embeddings, or agent-based analytics.
Ability to contribute to model deployment workflows (e.g., using Vertex AI, Airflow, or

📌 Data Scientist Mumbai (India)
🏢 Success Booster
📍 India