Head of Data Analytics & Science

Tasks

• Architect data pipelines
• Build cohort and LTV models
• Build credit scoring models
• Build data platform
• Build risk models
• Create dashboards and tools
• Define data governance
• Define data strategy
• Define performance metrics
• Design fraud detection engines
• Develop experimentation infrastructure
• Develop payment and hardware analytics
• Ensure data quality
• Hire and mentor talent
• Scale data team

Perks/Benefits

• Flexible work hours
• Health insurance
• Professional development budget
• Remote work options

Skills/Tech-stack

Credit Scoring | Data Architectures | Data Governance | Data Pipeline Development | Data pipeline | Data strategy | Deep learning | Flink | Fraud Detection | Kafka | LightGBM | Machine Learning | Pipeline Development | Python | Risk Modeling | SQL | Spark Streaming | Streaming Data | Streaming data architectures | XGBoost