The Data Scientist in this role will be primarily embedded within Wealthfront’s Fraud and Risk (F&R) team. All assets and clients entering in or exiting out of Wealthfront pass through F&R systems and checks. As such, F&R Engineers and Data Scientists have the dual responsibility of safeguarding our clients’ assets while maintaining a delightful experience for regular clients.
Potential project areas for this role include (but are not limited to) monitoring client signup flow, tagging anomalous financial transactions, automated classification of normal and fraudulent financial behaviors and helping evaluate security implications of product initiatives.
The F&R team relies heavily on production machine learning (ML) models to automate fraud detection. We constantly update our models and develop new ones to address the fast-evolving financial fraud landscape. The key desired traits for a Data Scientist in this role are an advanced ability to translate security-related problems into mathematical language, lead research and own the production deployment. An ideal candidate will also be able to explain technical choices and trade-offs to broad audiences in a simple language. Above all, we want candidates who possess a “security mindset” – a drive to be constantly aware of the potential for threats and being proactive in safeguarding our clients’ information and assets.
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.
Estimated annual salary range: $165,000 – $185,000 USD plus equity and a discretionary bonus.
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