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Staff Data Scientist, Fraud & Risk - Careers at Tide
Data Scientist
Lead the design and deployment of advanced fraud and risk analytics, leveraging Python, SQL, and machine learning on cloud platforms to protect SME customers and drive data‑driven decision making.
About the role
Key Responsibilities
- Design, develop, and productionize machine‑learning models for fraud detection, risk scoring, and anomaly identification.
- Collaborate with product, engineering, and compliance teams to translate business problems into analytical solutions.
- Build and maintain data pipelines and feature stores using SQL and cloud services (AWS) to ensure reliable, real‑time data for modeling.
- Perform statistical analysis and A/B testing to evaluate model performance and impact on key business metrics.
- Mentor junior data scientists and promote best practices in code quality, reproducibility, and model governance.
Requirements
- 5+ years of experience in data science or analytics, with a focus on fraud, risk, or security domains.
- Proficiency in Python (pandas, scikit‑learn, PyTorch/TensorFlow) and strong SQL querying skills.
- Hands‑on experience building and deploying ML models in cloud environments, preferably AWS (SageMaker, Lambda, Redshift).
- Deep understanding of statistical modeling, hypothesis testing, and experimental design.
- Excellent problem‑solving abilities and the capacity to communicate complex insights to non‑technical stakeholders.
Skills
pythonsqlmachine learningaws