Compunnel, Inc.
We are seeking a highly skilled Data Scientist to design and implement predictive models using high-dimensional, real-time datasets.
The ideal candidate will apply advanced machine learning and data mining techniques to detect fraud and abuse, support strategic decision-making, and contribute to innovation through research and patent filings.
This role requires strong technical expertise, storytelling with data, and experience in production environments.
Key Responsibilities
- Design, build, and deploy predictive models for fraud and abuse detection, including account takeover (ATO), membership fraud, trial abuse, LTO abuse, and bot attacks.
- Own fraud/abuse risks for specific products or segments and act as a strategic partner to product development teams.
- Communicate insights and recommendations effectively through data storytelling and visualization.
- Build interactive dashboards and visualizations for internal and external stakeholders.
- Apply ML/AI, deep learning, and data mining techniques to develop robust anomaly detection models.
- Contribute to research initiatives and US patent filings to address emerging fraud issues and automate processes.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field.
- Strong technical expertise in machine learning, statistical analysis, and data storytelling.
- Proficiency in Python and machine learning/data mining packages.
- Experience working with large datasets and distributed computing tools (GCP/BigQuery preferred).
- Experience with production deployment of models.
- Familiarity with GenAI and Agentic AI technologies.
- Experience in fraud detection or anomaly detection domains.
- Knowledge of cloud-native tools and services for scalable model deployment.
- Experience in patent filing or research-driven innovation.