Senior Data Scientist
Tasks
- Architect churn and intervention scoring models
- Architect next best action decisioning engine
- Build fraud model components
- Create model documentation and present results to stakeholders
- Define and execute online experiment designs and analyse results
- Design and build production grade agentic AI systems
- Lead next most likely product recommendation engine
- Own full lifecycle of complex modelling programmes
- Set and enforce model and MLOps technical standards
Perks/Benefits
- Free office snacks
- Health insurance
- Meal vouchers
- Multisport card
- Paid leave
- Public transport pass
- Training and development budget
- Unlimited course access
Skills/Tech-stack
A/B | A/B Testing | Agent Orchestration | Anomaly Detection | B testing | BigQuery | CI/CD | Causal Inference | Difference-in-differences | Drift monitoring | Feature Stores | Flink | GCP | Instrumental Variables | LLM Applications | LightGBM | Model Serving | Model registries | Multi-Agent | Multi-agent orchestration | Pandas | PyTorch | Python | RAG | Real Time | Real-time Inference | Recommendation Systems | SQL | Scikit-learn | Sequence Modelling | Spark Streaming | Streaming Data | Survival analysis | TensorFlow | Time Series | Uplift Experiments | Uplift Modelling | XGBoost
Education
Roles
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