Senior Data Scientist
Tasks
- Analyze fallback effectiveness
- Build channel economics unified performance metrics
- Build conversion propensity and routing models
- Build customer level unit economics visibility
- Build real time customer ROI metrics
- Build workflow optimizer recommendations
- Create customer segmentation models
- Create customer value dashboards
- Define canonical event schema and taxonomy
- Define monetization packaging and entitlements
- Design dashboard and data product delivery APIs
- Develop attribution models
- Develop fraud and abuse detection models
- Develop predictive channel routing models
- Develop verification intelligence data products
- Forecast time to verify for SLA commitments
- Implement data quality infrastructure
- Implement fraud protection analytics
- Model willingness to pay signals
- Monitor channel health and trigger alerts
- Own KPI narratives for margin growth and positioning
- Track data product attach rates retention and revenue growth
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | Airflow | Anomaly Detection | Anomaly Scoring | Apache Flink | B testing | CCPA | CI/CD | Causal Inference | Classification | DBT | Dagster | Data Contracts | Data Modeling | Data Pipelines | Feature Stores | GDPR | Idempotency | Instrumental Variables | Looker | MLOps | Machine Learning | Model Monitoring | Pandas | PySpark | Python | Real Time | Real-time Scoring | SQL | Scikit-learn | Semantic layer | Series analysis | Star Schema | Streaming Data | Streaming data pipelines | Survival analysis | Tableau | Time Series | Time Series Analysis | Uplift Modeling | Webhooks
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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