Quant Analytics Associate - Fraud Prevention

Embark on a rewarding and challenging career as a Quant Analytics Associate with our dynamic team. Join us and contribute to our mission while advancing your career. Here, you'll feel welcomed and valued. Our clients, transactions, deals and projects are global, so we work hard to create diverse, inclusive teams that support our business and each other.  

As a Quant Analytics Associate – Fraud Prevention within the Fraud Prevention Operations Optimization Analytics & Strategy team, you will support different products like Card, Retail and Digital, in optimizing for losses, customer experience and efficiency, through strategy recommendations.  You will work closely with peers in different groups within Strategy and Operations across the life cycle to support products like Zelle, Wires, Bill Pay etc. and help them manage ATO, Wrong doer, Scams etc.

Job responsibilities:

• Develop and maintain code-driven data and monitoring solutions using languages such as SQL, SAS, and Python, including data extraction and querying, transaction/alert/claim trend monitoring, and performance analytics to optimize tool behavior and rules strategy
• Monitor and maintain fraud authorization strategies to counter emerging attacks and trends across loss types, reduce false positives, support both card-present and card-not-present channels, and meet overall budget goals.
• Collaborate closely with Operations to understand product policies and procedures and improve decision quality as needed.
• Identify key drivers of customer pain points and partner with the broader Operations team to develop creative solutions.
• Conduct deep dives across processes to identify gaps, efficiency opportunities, and leakage-prevention measures.
• Partner with Strategy to optimize ATO, wrongdoer, and scam strategies and support controlled channel expansion (e.g., Challenge as a Service) to drive optimal outcomes across key portfolio segments and deliver profitable ROI.
• Develop new model input variables and profiles, and expand the data footprint, pattern-detection techniques, and related capabilities to improve authorization decision accuracy across functions.
• Partner with Claims, Recovery, and Customer Experience teams to improve recovery outcomes and reduce provisional credit theft.
• Ensure compliance with the existing control framework and drive enhancements that enable successful closure of strategy audits and Matters Requiring Attention (MRAs).
• Present clear, concise narratives by translating complex data and analysis into executive-ready materials for senior leaders and influencing outcomes across forums.

Required qualifications, capabilities and skills:

• 2 years of work experience in risk management, strategic analytics, data analytics or payments function from a banking or consulting domain
• Competent in the use of data technology to solve complex business problems, with hands-on expertise in the use of programming languages like LLM, Python/Hive, SAS, R, SQL, Unix and/or other Oracle and/or Teradata database tools 
• Experience in Big Data platforms and technologies (Hadoop, Hive, Pig, Spark, etc.) & Machine learning
• Strong communication, influencing and interpersonal skills with ability to interact with individuals across departments / functions and making recommendations to Senior management
• Good multi-tasking skills with ability to manage and prioritize projects across cross-functional groups
• Ability to thrive in a dynamic and fast-paced energetic environment and can adapt to changes quickly
• Bachelors degree or work experience equivalent

Preferred qualifications, capabilities and skills:

• Master's  degree in relevant technical or quantitative fields (e.g. Mathematics, Engineering, Finance, Business, Statistics, Operations Research and Economics) with strong analytical, technical, statistical skills preferred