Job Description
We are accelerating two high-priority fraud detection and prevention initiatives. Need someone with in-depth data engineering and ML engineering experience and data science skillsets are nice to have.
What You’ll Do
- Prepare and clean datasets from internal and partner sources for Machine Learning models
- Run and support unsupervised models (e.g., Isolation Forest, K-Means, DBSCAN) on baseline and partner data for anomaly detection and behavioural clustering
- Compare results to current integrity scoring approaches
- Build clear visualizations and concise summaries of baseline behaviours, clusters, and fraud patterns for executive and partner consumption
- Consolidate findings across univariate/bivariate/multivariate and ML analyses into structured outputs (slides, notes, notebooks)
- Document assumptions, transformations, and model configurations to ensure reproducibility
Must-Have Skills & Experience
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