Mission Lane

Data Scientist

• Innovate and improve machine learning models for financial progress
• Collaborate on designing, developing, and deploying machine learning models
• Partner with business leaders and technical experts to develop new data sources
• Apply models with sound risk management

Senior Data Scientist, Credit

Manager

• Responsible for building and maintaining financial models and projections related to funding and capital raise activities by leveraging cutting edge technology including AI
• Build cutting edge financial models and tools to evaluate funding alternatives
• Partner with Credit, Data and FP&A teams to assist the development of new and existing capital markets activities
• Structure debt and equity strategies and evaluate capital structure decisions
• Set up tools to generate investor materials
• Present to investors and senior management

Capital Markets Manager

• Lead a data science team and cross-functional projects
• Innovate and improve machine learning models
• Partner with business leaders and technical experts across the company
• Develop new data sources and improve our modeling methodology
• Apply models with sound risk management

Director of Data Science, Credit Risk

Business Analyst

• Analyze and Investigate Fraud Trends: Dive deep into application data to proactively identify emerging fraud patterns, uncover system vulnerabilities, and understand the evolving tactics used by criminals.
• Develop and Fine Tune Fraud Strategies: Design, build, and implement new, real-time defenses to detect and prevent fraudulent applications. You will constantly test and refine our strategies to stay ahead of fraudsters.
• Balance Risk with Customer Experience: Make thoughtful, data-backed decisions that strike the optimal balance between risk prevention and customer experience.
• Monitor and Report on Performance: Create and maintain robust dashboards to track the performance of fraud strategies. You’ll be responsible for reporting on key metrics like coverage, pause rates, step-up completion rates, defense performance, and losses.
• Optimize and Collaborate: Work closely with our Operations, Product, Data Science, and Engineering teams to continuously improve fraud detection capabilities and strategies.

Principal Business Analyst, Fraud

General Counsel

• Owning day-to-day legal advice on collections, recoveries, and servicing.
• Negotiating and closing contracts with debt sale counterparties, vendors, and technology providers.
• Tracking legal and regulatory developments as they land, including the fast-moving rules around AI in back-office and customer-facing tools, and helping the business turn them into compliant products, services, and controls.
• Partnering directly with the business on new initiatives that improve the servicing and collections experience, and with Compliance and Risk to sharpen consumer communications and internal processes alike.
• Spotting where the business is headed before it gets there, flagging issues and opportunities early.

Associate General Counsel – Collections, Servicing and Customer Operations

Operations

• Set the 3-year vision and strategy for both customer-facing servicing and back office fulfillment, building the roadmap largely on your own.
• Own the day-to-day: keeping resolution speed, quality scores, cost and efficiency, and associate engagement on target, and stepping in with a remediation plan the moment any of them slip.
• Build a team, in-house and through our contact center partners, that people want to stay and grow in.
• Become the person the SVP and other senior leaders call when they need a read on where servicing should go next.

Senior Director, Servicing Operations

Artificial Intelligence

• Own Mission Lane's operations AI agenda from strategy through execution
• Develop and deliver an AI Operations strategy from the ground up
• Identify problems where meaningful AI solutions exist and evaluate vendors
• Work with cross-functional teams across Product, Engineering, vendors, and Operations to execute it
• Measure success based on outcomes that matter, including cost, quality, and customer experience

Senior Operations Manager, AI

Compliance

• Own fraud, collections, and back-office compliance for Mission Lane's credit card business
• Be the embedded compliance authority across Mission Lane's fraud, collections, and back-office servicing operations
• Own day-to-day escalations from fraud and collections
• Run testing and monitoring against critical controls
• Proactively identify gaps and develop guidance on high-risk compliance topics
• Partner with the business to strengthen programs and elevate the expertise of the compliance team

Compliance Manager

Marketing Operations

• Own the systems, processes, and team behind our direct marketing function
• Ensure the offers that make these moments possible are delivered precisely, every time
• Document the business process, running, and earning trust from the teams who feed into it
• Tag, name, and make assets findable
• Improve campaign cycle times and provide leadership with campaign visibility
• Identify automation opportunities across the workflow and implement them
• Build the operational foundation as the function expands into digital channels.

Senior Manager, Marketing Operations

Data Analyst

• Architect and maintain high-fidelity, scalable data models that serve as the foundational truth for both enterprise business intelligence and GenAI applications.
• Partner with data engineering, product and business partner teams to define, design, analyze, and report on key drivers that impact performance across the organization.
• Identify and communicate the business relevance of data from across the organization, leveraging analytical rigor to establish reliable sources of truth and ensure that business context is accurately captured across all data products.
• Partner with the larger Data organization to design easy-to-use, end-to-end enterprise data systems that keep Mission Lane at the forefront of data -based decision-making.
• Own the development of self-serve analytics and strategic data products that look beyond the immediate stakeholder requests to proactively reduce manual effort, mitigate technical debt, and accelerate speed to insight.
• Define and champion technical standards for analytics engineering to elevate the quality, reliability, and impact of work produced by the broader analytics team.