Data Scientist
Tasks
- Build LLM agentic workflows
- Build ML models
- Collaborate with business stakeholders
- Communicate experimental findings
- Design end-to-end ML pipelines
- Detect data drift and data quality issues
- Develop CLTV and churn models
- Develop fraud detection models
- Implement next best action decisioning
- Monitor deployed models
- Support A/B experiments
Perks/Benefits
- Annual training budget
- Dental insurance
- Employer pension contribution
- Group life assurance
- Health insurance
- Performance bonuses
- Promotion opportunities
- Teambuilding activities
- Unlimited LinkedIn Learning access
Skills/Tech-stack
A/B | A/B Testing | B testing | Batch inference | Bias Mitigation | BigQuery | Classification | Clustering | Data Drift | Data Quality | Feature Engineering | Fraud Detection | Function Calling | GCP | LIME | LLM APIs | Langchain | LightGBM | Llamaindex | MLflow | Machine Learning | Model Deployment | Model Evaluation | Model Serving | Multi-Armed Bandit | NumPy | Pandas | PyTorch | Python | RAG | REST APIs | Regression | Responsible AI | SHAP | SQL | Scikit-learn | Supervised Learning | Survival analysis | TensorFlow | Time Series | Unsupervised Learning | Uplift Modeling | Weights and Biases | XGBoost
Education
N/A
Roles
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