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Job Description 

Responsible for leading a research group within MRM to develop frameworks, tools, and guidelines to manage the risks of using AI & Machine Learning models in the business and to prepare DFS for the next stage of advanced machine learning techniques.

What You’ll Do

• Develop vision, strategy and roadmap for MRM ML research and innovation to stay ahead of the rapidly evolving nature of ML model validation activities.
• Establish group as a knowledge center that accumulates and analyses insights from multiple AI/ML sources with the ultimate goal of flagging emerging ML model risk to drive value.
• Provide technical leadership to the research team in evaluating new emerging technologies for practical implementation either through independent research or collaborative work.
• Collaborate with other teams - within MRM (model validation and model governance), Decision Management (DM), and Corporate Risk Management (CRM) to set up best practices, innovative solutions and automation (e.g. benchmark algorithms, build custom explainers, etc.) to drive effective and efficient validation outcomes.
• Publish research articles, findings and working papers for both internal DFS consumption and for presentations at industry Model Risk Management and AI/ML conferences.
• Conduct peer review of key machine learning models to ensure consistency and robustness of validation activities. Support regulatory and IA exams on AI/ML models
• Provide training and problem solving sessions for MRM teams on emerging AI/ML issues.
• Support governance team in updating related standards, procedures and templates to reflect current and evolving AI/ML practices
• Monitor the state of usage of machine learning & AI across the company and present proper strategies to manage associated risks to the senior leadership team, model risk committee and executive members of the company.
• Conduct validation when required and use such validation opportunities to drive and focus research

How You’ll Do It

• Provide thought leadership & strategic thinking to translate business problem into analytical framework(s) and independently recommend actions and provide business insights. Lead the development and implementation of advanced analytics including customer segmentation, optimization, prescriptive analytics and machine learning algorithm & recommendation to solve business problems.
• Operate as a subject matter expert on statistical analysis, test and design of experiment, analysis methodology, modeling & application and financial impact analysis.
• Establish and maintain effective performance tracking; identify improvement opportunity, form hypothesis, proposes, designs and implement tests to drive strategy enhancement and optimization.
• Recruit, train, coach and develop talent to their full potential with exceptional quantitative/analytical competencies, as well as project management skill and leadership skills. Manage and set priorities of analyst, assign projects and allocate resource, communicate business performance and project progress to management & business partners.
• Collaborate 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. Deliver effective presentations of findings and recommendations to multiple levels of leadership, creates visual displays of quantitative information. Facilitate implementation of work product and ensure accuracy.
• Ensure standard work processes and documentation requirements are timely and consistently followed by team. Encourage continuous improvement of team processes and share across functional teams to ensure consistency.

Qualifications You’ll Need

The Basics

• Bachelor’s Degree in Analytics, Engineering, Statistics or related field
• 8+ years of experience in Data Science, Credit Risk, Fraud Risk, Marketing Analytics, Optimization, Operations Analytics, Modeling or related field
• 2+ years of experience in People Management

• Proven experience in team leadership, ability to recruit and develop staff with diverse backgrounds and in different geographic locations, ability to allocate resources based on priority and skill level, strengths, and area of expertise.
• Proven ability to train and mentor junior colleagues and develop their careers.
• Proven ability to establish and maintain collaborative relationships with non-analytic business partners, including executive leadership, in order to elicit business needs and formulate, propose and refine solutions in order to meet the business needs and to drive efficiency and effectiveness improvements and business value.
• Excellent written and oral communication skills, ability to tailor the communication style to each specific audience.
• Excellent project management skills with ability to lead and engage in multiple projects and initiatives and appropriately prioritize her/his own time as well as that of the direct reports.

Preferred Qualifications

• Master’s or higher Degree in Analytics, Engineering, Mathematics, Statistics or related field
• 6+ years of experience in Data Science, Credit Risk, Fraud Risk, Marketing Analytics, Optimization, Operations Analytics, Modeling or related field
• Solid theoretical understanding of machine learning, deep learning, and reinforcement learning.
• Strong background in statistical languages technologies (e.g. R, SAS) and experience in open source languages (Python, Spark)
• At least 2 years’ experience working with a cloud platform (e.g. AWS, Azure) –
• Publications in relevant top-tier peer-reviewed journals.

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What are you waiting for? Apply today!

The same way we treat our employees is how we treat all applicants – with respect. Discover Financial Services is an equal opportunity employer (EEO is the law). We thrive on diversity & inclusion. You will be treated fairly throughout our recruiting process and without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status in consideration for a career at Discover.