Lead Data Science Analyst, Fraud Servicing Strategy

Key Skills

Data science techniques, Data Modelling, Fraud Risk, Credit Risk, Operations Analytics

Job Description

With us, you’ll do meaningful work from Day 1. Our collaborative culture is built on three core behaviors: We Play to Win, We Get Better Every Day & We Succeed Together. And we mean it — we want you to grow and make a difference at one of the world's leading digital banking and payments companies. We value what makes you unique so that you have an opportunity to shine.

Come build your future, while being the reason millions of people find a brighter financial future with Discover.

Job Description

An exciting opportunity exists to join our fast-paced Fraud Risk Servicing Strategy team which focuses on applying analytical and capability/process improvement discipline to advance customer-facing, agent-facing, and automated processes to drive meaningful reductions in fraud losses and operational costs, a seamless customer and agent experience, while ensuring a robustly governed, compliant, flexible, and modern end-to-end process serving millions of credit card and bank product consumers.

Responsible for working closely with management to execute analytical initiatives. Responsible for solving business problem by leveraging techniques such as segmentation, optimization, advanced analytics and machine learning. Creates reports and dashboards to closely monitor performance metrics and provide insights.

Responsibilities

• Continuously drives improvement in effectiveness, efficiency, and experience within owned processes by identifying opportunities/gaps, performing analyses to assess, recommending, testing, and deploying process/procedure/capability enhancements including new vendor verification tools, and monitoring results and ongoing process health for servicing of detected fraud concerns. Role emphasis will be first party fraud verification processes for credit card product. 
• Plays instrumental role in forging common streamlined and effective verification principles, methods, tools, procedures, and platforms across card and bank products at application and post-acquisition stages.
• Ensures strong operational excellence through process control assessments, ongoing change management, and close consultation with Law and Compliance
• Leads the development and implementation of advanced analytics including customer segmentation, optimization, prescriptive analytics and machine learning algorithm & recommendation to solve business problems. Operates as a subject matter expert on statistical analysis, test and design of experiment, analysis methodology, modeling & application, and financial impact analysis.
• Collaborates with cross-functional partners to understand their business needs, formulate and complete end-to-end analysis that includes data gathering, analysis, ongoing scaled deliverables and presentations. Delivers effective presentations of findings and recommendations to multiple levels of leadership, creating visual displays of quantitative information.
• Establishes and maintains effective performance tracking; identify improvement opportunity, form hypothesis, proposes, designs and implements tests to drive strategy enhancement and optimization.
• Manages multiple priorities, communicate business performance and project progress to management & business partners.
• Develops and automates reports, iteratively build and prototype dashboards to provide insights at scale, solving for analytical needs. Facilitates implementation of work product and ensure accuracy.
• Consistently follows standard work processes and documentation requirements. Recommends improvement to work processes to increase efficiency while maintaining quality of work.
• Continuously improves technical and leadership skills through training and development.

Minimum Qualifications

At a minimum, here’s what we need from you:

• Bachelor's Degree in Analytics, Engineering, or Statistics
• 4+ years of experience in Credit Risk, Fraud Risk, Marketing Analytics, Optimization, Operations Analytics, Modeling/Data Science or related.

Preferred Qualifications

If we had our say, we’d also look for:

• Master's Degree in Analytics, Engineering, or Statistics
• 2+ years of experience in Credit Risk, Fraud Risk, Marketing Analytics, Optimization, Operations Analytics, Modeling/Data Science or related
• Ability to thrive in fast-paced, rapidly evolving environment
• Experience in negotiating win-win solutions across stakeholders
• Direct/indirect experience in customer servicing environment