Data Scientist II - Fraud Prevention and Detection

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Job Summary:

This job is responsible for performing more complex analysis aimed at improving portfolio risk, profitability, performance forecasting, and operational performance for consumer products and related divisions, such as credit cards. Key responsibilities include applying knowledge of multiple business and technical-related topics and independently driving strategic improvements, large-scale projects, and initiatives. Job expectations include working with business counterparts within the Line of Business and partner organizations including Risk and Product teams.

Fraud Prevention and Detection is looking for an energetic and inquisitive experienced data scientist to join our team and help us combat financial crime using graph databases. In this role, you will be expected to work on large and complex data science projects. Collaborating with internal strategy, technology, product, and policy partners to deploy advanced analytical solutions with the goal of reducing fraud losses, lowering false positive impacts, improving client experience, and ensuring the Bank minimizes its total cost of fraud.

Responsibilities:

• Link Analysis/Graph analytics to find and mitigate densely connected fraud networks.
• Developing and tuning graph algorithms to maximize detection of fraud.
• Work with software developers to create/enhance link analysis process for new fraud detection use cases, and assist with the generation, prioritization, and investigation of fraud rings.
• Coordinate with stakeholders and tech to deliver process end-to-end, be the gate keeper for issue tracking and remediation.
• Gather business requirements and translate to technical logic for script development, and design, create and monitor daily report/QA metrics for fraud detection process.
• Document and prepare attestation response for process and fraud strategy with governance team.
• Identify, track, and recommend opportunities for process improvement.
• Coach and mentor peers to improve proficiency in a variety of systems and serve as a subject matter expert on multiple business and technical-related topics.
• Identify business trends based on economic and portfolio conditions and communicate findings to senior management.
• Support execution of large-scale projects, such as platform conversions or new project integrations by conducting advanced reporting and drawing analytics-based insights.

Required Qualifications:

• 5+ years of experience in data and analytics is required.
• Must be proficient with SQL and one of SAS, Python, or Java
• Critical problem-solving skills including selection of data and deployment of solutions.
• Proven ability to manage projects, exercise thought leadership and work with limited direction on complex problems to achieve project goals while also leading a broader team.
• Excellent communication and influencing skills.
• Thrives in fast-paced and highly dynamic environment.
• Intellectual curiosity and strong urge to figure out the “whys” of a problem and come up with creative solutions.
• Model development experience leveraging supervised and unsupervised machine learning (regression, tree-based algorithms, neural networks)
• Expertise handling and manipulating data across its lifecycle in a variety of formats, sizes, and storage technologies to solve a problem (e.g., structured, semi-structured, unstructured; graph; hadoop; kafka)

Desired Qualifications:

• Advanced Quantitative degree (Masters or PhD)
• 7+ years of experience; work in financial services is very helpful, with preference to fraud, credit, cybersecurity, or other heavily quantitative areas.
• Understanding of advanced machine learning methodologies including neural networks, ensemble learning like XGB, and other techniques
• Proficient with H2O or similar advanced analytical tools

Skills:

• Analytical Thinking
• Business Analytics
• Data and Trend Analysis
• Fraud Management
• Problem Solving
• Collaboration
• Innovative Thinking
• Monitoring, Surveillance, and Testing
• Presentation Skills
• Risk Management
• Data Visualization
• Interpret Relevant Laws, Rules, and Regulations
• Issue Management
• Oral Communications
• Written Communications