Risk Analytics Consultant - Credit / Fraud Risk Strategy, Credit Cards, SAS

About this role:

Wells Fargo is seeking a Risk Analytics Consultant.

In this role, you will:

• Participate in less complex analysis and modeling initiatives, and identify opportunity for process production, data reconciliation, and model documentation improvements within Risk Management
• Review and analyze programing models to extract data, and manipulate databases to provide statistical and financial modeling, and exercise independent judgment to guide new and existing projects with medium risk deliverables
• Coordinate and consolidate the production of monthly, quarterly, and annual performance reports for more experienced management
• Present recommendations for resolving data reconciliation, production, and database issues
• Exercise independent judgment while developing expertise in policy governance, risk projects, and regulatory requests
• Collaborate and consult with peers, managers, experienced managers, compliance, including various lines of business.

Required Qualifications:

• 2+ years of Risk Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education.

Desired Qualifications:

• The Consumer Lending Credit Card Fraud & Auth risk team is responsible for leading, developing and implementing strategic initiatives and processes to drive the fraud & credit loss mitigation and enhance customer experience. The team is seeking a highly motivated and talented individual to be part of the Consumer Lending Credit Card team.
• Primary role is to apply strong business knowledge and analytical skills to solve business questions, think out-side-of-the-box and develop innovative yet practical risk management strategies impacting the bottom line of the business. An individual who is results driven, goal oriented, and enjoys a fast-paced working environment will find this opportunity both challenging and exciting.
• Responsibilities
• The incumbent would functionally contribute as a part of Credit Authorization team to support Consumer Lending Credit Cards Risk team and execute relatively large and complex projects with moderate to high risk for the line of business.
• Works in significant initiatives and processes, and partners with line of business management to drive the company risk management culture and business performance with inputs from senior leadership.Acts as an analyst for senior leaders with regard to any requests.
• Assesses and predicts risk and performance through business analysis and/or modeling.Establishes effective policies, processes, and tools to identify and manage risks. Uses predictive sciences for developing future ready solutions.
• Assists in development of predictive strategies / solutions for credit authorization strategy. Analyzes big transaction data and understand / monitor trends to provide actionable insights across a range of risk analytics initiatives.
• Develops comprehensive monitoring frameworks and dashboards and provide statistically sound diagnostic evaluation of any emerging or unexpected risk areas to enhance intelligence and facilitate faster decision making.
• Develop new and enhance existing models/prototypes for managing fraud risk, payment risk, credit bust outs etc. Evaluate new data sources and attributes, internal and external from extensive case reviews for efficacy in models.
• Develop complex programming models to extract data and/or manipulate databases such as ORACLE, Teradata.
• Ensures resolution of matters requiring attention (MRA) from outside regulators, Audit, Corporate Model Risk or internal review teams. May partner with other business units, Audit, Legal, regulators, and industry partners on risk related topics.
• To be effective in this position, you will need to have a good understanding of credit/fraud, practice in the test and learn discipline and exploratory analysis and be fluent in both the key technical tools of credit risk decisioning and sound credit/fraud judgment.
• Bachelor's degree or higher in a quantitative field such as applied mathematics, statistics, engineering, finance, economics, econometrics or computer sciences.
• 2+ years of progressive experience in credit and risk analytics roles.
• Hands on Experience in at least one area in credit risk analytics - credit strategy / modeling techniques / Forecasting techniques / data architecture & management.
• Good understanding of risk domain Strong Risk analytics skills and understanding of P&L, drivers.
• Expertise in few programming and statistical packages - SAS, SQL, Macros, R, Python, E-miner, Tableau.
• Knowledge of advanced statistical tools such as Segmentation Tools, Decision Trees, Clustering, Regression, and other statistical modeling and/or Machine Learning techniques.
• Strong analytical skills with ability to turn findings into executable plans to meet business objectives.
• Ability to identify and evaluate trends, isolate root cause, and provide swift/thorough resolution.
• Knowledge and understanding of (consumer lending) credit card lending practices, policies, procedures, and key drivers impacting credit offerings
• Ability to contribute to strategic decisions and coordinate with multiple stakeholders. Develop consensus and gain buy-in for strategic priorities, meet deadlines, achieve goals, and work under pressure in a dynamic and complex environment.
• Strong ability to develop partnerships and collaborate with other business and functional area.

Job Expectations:

• Advanced degree in statistics/finance /engineering/economics/other quantitative disciplines.
• Shift timings: 1:30 PM to 10:30 PM.

Posting End Date:

Applicants with Disabilities

To request a medical accommodation during the application or interview process, visit.

Drug and Alcohol Policy

Wells Fargo maintains a drug free workplace. Please see our to learn more.

Wells Fargo Recruitment and Hiring Requirements:

a. Third-Party recordings are prohibited unless authorized by Wells Fargo.

b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.