Data science intern analyzing HR data and developing predictive models and AI solutions. Supporting iA Financial Group’s insurance, savings, and wealth management business.
About the role
- Senior Data Scientist developing production fraud-detection models and investigating attacks. DataVisor provides AI-powered fraud and AML risk software for global enterprises.
Responsibilities
- Lead the full lifecycle of fraud detection features and models, from ideation and data exploration to prototyping, productionizing, and monitoring.
- Develop predictive features from large-scale, multi-dimensional data, including user behavior, device intelligence, network graphs, and transaction records.
- Process massive, noisy, and imbalanced datasets using Spark, SQL, and the proprietary AI platform.
- Leverage agentic AI to automate analytic pipelines and develop reusable tools for fraud investigation, feature generation, and reporting.
- Lead investigations into complex fraud cases across identities, accounts, devices, and transaction surfaces.
- Reconstruct attacker sequences and hypothesize actor intent and tooling.
- Produce evidence-backed technical reports and case studies for product, engineering, operations, legal, and executive stakeholders.
- Generate customer-facing fraud trend reports by synthesizing case-level findings and aggregate data.
Requirements
- Master's or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.
- 3+ years of applied experience in fraud detection, cybersecurity, or a related adversarial/high-velocity risk domain (fintech, consumer payments, banking, SaaS, marketplace risk, or security research).
- Solid understanding of both classic machine learning models (Logistic Regression, Gradient Boosting, etc.).
- Hands-on experience with the machine learning lifecycle in a production environment.
- Investigator mindset: demonstrated skill in pattern synthesis, hypothesis testing, and triaging signal from noise in ambiguous, adversarial cases — not just building and monitoring models.
- Strong programming skills in Python (must-have) and proficiency with SQL; experience with PySpark is a significant plus.
- Experience with large-scale data tools (Spark, Hadoop, etc.) and cloud platforms (AWS, GCP, Azure).
- Excellent communication skills — able to explain complex, ambiguous, or technical behavior clearly to both technical and non-technical audiences, including customers and executives.
- Professional proficiency in written and spoken English, with the ability to collaborate effectively in a global, cross-functional team.
Benefits
- PTO
- Stock Options
- Health Benefits
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