Lead Quantitative Analytics Specialist
Wells Fargo is hiring a Lead Quantitative Analytics Specialist in Bengaluru, India. Level rates it ; you can apply on Wells Fargo.
Level's read on this job
- On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
- Level classifies it as a lead role.
- Level lists 1,500+ other open roles at Wells Fargo.
- The role was posted in the last few days.
AI in this role
About this role:
Wells Fargo is seeking a Lead Quantitative Analytics Specialist for Credit Risk modelling for Retail and commercial portfolio.
In this role, you will:
- Lead complex initiatives including creation, implementation, documentation, validation, articulation, and defence of highly statistical theory
- Use highly complex statistical theory to quantify, analyze and manage markets
- Forecast losses and compute capital requirements providing insights, regarding a wide array of business initiatives
- Utilize stochastic, structured securities, spread analysis, with the expertise in the theory and mathematics behind the analysis
- Review and assess models inclusive of technical, audit, and market perspectives
- Manage market, credit, and operational risks to forecast losses and compute capital requirements
- Participate in the discussion related to analytical strategies, modeling and forecasting methods
- Identify structure to influence global assessments, inclusive of technical, audit and market perspectives
- Collaborate and consult with regulators, auditors and individuals that are technically oriented and have excellent communication skills
- Development of regulatory Credit risk (including CCAR, CECL and IFRS), RRP Valuation, and PPNR models for Commercial portfolio in SAS/Python.
- Work closely with other team members to understand and enhance the data and modeling process behind existing models, develop new models, address data and model issues/findings.
- Underlying portfolio data research and analytics using strong programming skills
- Adhere to audit and model validation governance to ensure data and modeling process are in compliance with policy and are working as intended, address model validation and regulatory feedback issues
- Support ad-hoc analytic projects
Required Qualifications:
- 5+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, education.
- Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science
- Experience in development of regulatory model (including CCAR, CECL and IFRS), RRP Valuation, and PPNR models for Commercial portfolio
- Good Written and Oral Communication Skills
- Ability to prioritize work, meet deadlines, achieve goals and work under pressure in a dynamic and complex environment
- Detail oriented, results driven, and has the ability to navigate in a quickly changing and high demand environment while balancing multiple priorities
- Understanding of bank regulatory data sets and other industry data sources
- Exposure to banking domain with strong functional knowledge in Credit Risk area on Commercial portfolio
Strong Quantitative Skills:
- 5+ years of Predictive modeling experience. Good understanding of model development and model testing.
- Proficient in statistical analysis
- Good Problem Solving and Analytical Skills.
Programming Skills:
- 2+ years of hands-on experience in Python and SQL
- 2+ years of experience in PySpark, GCP, parallel processing.
- Comfortable with Git, GitHub and UNIX commands
Job Expectations:
- Shift timings: 1:30 PM to 10:30 PM
- in office expectations: 4 - days a week
Posting End Date:
28 Oct 2026*Job posting may come down early due to volume of applicants.
We Value Equal Opportunity
Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements.
Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.
Applicants with Disabilities
To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.
Drug and Alcohol Policy
Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy 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.
How we rate this
Lead Quantitative Analytics Specialist at Wells Fargo rates 34 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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