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Data Scientist
Forbes Advisor
Not specified · onsite · Posted 89d ago
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Section · 01
About this role
We're hiring a Data Scientist to help us unlock growth through advanced analytics and machine learning. This role sits at the intersection of marketing performance, product optimisation, and decision science. You'll partner closely with paid media, product, and engineering to build models, generate insight, and influence how we acquire, retain, and monetise users. From campaign ROI to user segmentation and funnel optimisation, your work will directly shape how we grow. This role is ideal for someone who thrives on business impact, communicates clearly, and wants to build re-usable, production-ready insights, not just run one-off analyses.
The core responsibilities for the job include the following:
Marketing and Revenue Modelling:
- Own end-to-end modelling of LTV, user segmentation, retention, and marketing efficiency to inform media optimisation and value attribution.
- Collaborate with Paid Media and RevOps to optimise SEM performance, predict high-value cohorts, and power strategic bidding and targeting.
Product and 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 and 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 and 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 into strategic action plans.
- Work cross-functionally with Engineering, Product, BI, and Marketing to deliver and deploy your work.
Requirements:
- Bachelor's 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, and 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 Composer).
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Section · 02
Skills
Section · Company
About Forbes Advisor

Forbes Advisor
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