Staff Data Scientist

We are seeking a passionate and innovative Data Scientist to join our Compliance Team—a role with immense potential to shape the future of our fraud prevention strategies. As a key player, you will intimately understand the operational context of our fraud, risk, and AML (Anti-Money Laundering) controls, addressing both logic-based rules and integrating existing or future machine learning models.

Your work will involve approaching business problems analytically, transforming complex fraud challenges into mathematical solutions that enhance the accuracy and efficiency of our systems. By leveraging your deep understanding of statistics and machine learning, you will extract valuable insights from intricate data sets, directly impacting our ability to develop actionable strategies and reinforce our commitment to providing a seamless experience for our customers and developers.

Key Responsibilities:

Statistics and Machine Learning: Apply a deep understanding of statistics and machine learning algorithms specifically tailored for fraud detection and modeling of rare events.

• Define model parameters using the appropriate algorithms and optimization techniques.

• Conduct model training and evaluation, focusing on validation, parameter tuning, and performance monitoring.

• Build pipelines and scalable CI/CD systems for machine learning models to maintain performance, detect feature drift, and respond to new patterns in the data.

• Realize machine learning models from conception to production, in collaboration with compliance engineers.

Data Storytelling: Extract actionable insights to narrate the underlying story and trends of fraudulent transactions and behaviors.

Data Acquisition and Transformation: Identify, source, and integrate new data from external repositories, new data sourced from our customers, and other sources ensuring comprehensive coverage to enhance analytical rigor.

Actionable Recommendations: Translate your findings into clear, action-oriented recommendations to product, navigating variable data quality to propose robust strategies for risk mitigation.

Monitoring and Reporting: Develop and maintain dashboards, reports, and alerts that track the performance of our fraud detection systems, analyzing their effectiveness from multiple dimensions.

Qualifications

• 9+ years experience in data science and machine learning with a strong emphasis on fraud detection or risk analysis.

• Proficiency in statistical analysis and machine learning, with hands-on experience in building, validating, and deploying models.

• Familiarity with data manipulation tools and programming languages (e.g., Python, SQL).

• Experience with data visualization tools and techniques to communicate insights effectively.

• Understanding of payment systems, cryptocurrency, or stablecoin ecosystems is a plus, but not mandatory.