2027 Quantitative Analytics Program Risk Analytics and Decision Science Masters Early Careers
Wells Fargo is a financial services company providing banking, lending, credit card, investment, wealth management, commercial banking, and corporate and investment banking services to consumers, businesses, and communities.
About Wells Fargo
Wells Fargo offers checking and savings accounts, credit cards, home and personal loans, auto loans, digital banking, payments, investment and wealth management, commercial banking, and corporate and investment banking. Its services support personal customers, small businesses, commercial clients, and institutional customers, with additional customer support through branches, ATMs, online banking, and the Wells Fargo Mobile app.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will apply advanced analytics, artificial intelligence, and machine learning to risk analytics and decision science challenges. You will forecast portfolio losses and revenue, develop credit scorecards, identify money laundering patterns, predict operational losses, and validate model design, calibration, and implementation.
Requirements
- 6+ months of work experience or equivalent experience, training, military experience, or education
- Currently pursuing a Master's degree in Statistics, Data Science, Mathematics, Econometrics, Computer Science, Engineering, or a related quantitative field
- Expected graduation date between December 2026 and June 2027
- Programming skills in Python, R, SQL, Spark, and Java
- Quantitative and analytical skills
- Data analysis, modeling, visualization, statistics, research, and generative AI skills
- Data and software engineering skills
- Data management skills
- Communication skills
- Business acumen
- Risk assessment and risk control knowledge
- Experience with machine learning and artificial intelligence models, data analysis, statistical modeling, data management, and computing
Responsibilities
- Forecast loss and revenue for credit card loan portfolios
- Develop credit scorecards for consumer decisioning strategies
- Build models to identify money laundering patterns across transaction databases
- Predict operational losses using statistical and machine learning modeling
- Validate model design, calibration, and implementation
- Design and deploy models for credit risk, financial crime, customer experience, and operations
- Apply generative AI to underwriting and customer interactions
- Detect fraud and optimize strategies
- Support risk assessments and apply risk controls
Benefits
- 12-month development program
- Mentorship
- Technical training
- Exposure to senior leaders
- Two six-month rotations
