Responsibilities:
- Translate known or newly discovered security-related scenarios into mathematical problem statements.
- Formulate project plans with clear rationale, candidate approaches and milestones.
- Quantify performance of fraud detection models using appropriate metrics (accuracy, precision, recall) before and after production deployment.
- Employ a high degree of mathematical rigor and best practices for software development.
- Work with F&R leadership to propose and implement new security enhancements for our products.
- Work with cross functional stakeholders to evaluate security implications for proposed new products or features.
- Work with Data platform teams to procure required (but unavailable) data.
- Explain technical choices, model limitations and trade-offs in a cross functional risk evaluation forums.
- Enhance overall Data Science team execution through hands-on help, design feedback and peer review.
Requirements:
- A Masters or a PhD degree in Computer Science, Statistics, Operations Research, or Natural Sciences with 4+ years of prior experience in a Data Science role. Exceptions to these requirements may be considered on a case-by-case basis.
- Prior experience in financial fraud detection and prevention is preferred, but not required.
- Strong communication and collaboration skills and a record of partnering across organizations to sharpen project requirements. Sometimes this includes re-framing the original request to solve a more general problem with similar effort.
- Hands-on mathematical and software engineering skills to execute on complex projects.
- Proficiency in Python and SQL.
- Desire and ability to mentor junior Data Scientists within the team by exemplifying math, engineering and technical communication skills.
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