Data Scientist

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 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 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.
• 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.
• Experience with GA4, Google Ads, Meta, or other performance marketing platforms.
• Clear 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