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Wells Fargo

Lead Quantitative Analytics Specialist

Posted 10 Hours Ago
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Hybrid
Bengaluru, Bengaluru Urban, Karnataka
Senior level
Hybrid
Bengaluru, Bengaluru Urban, Karnataka
Senior level
Lead development and governance of quantitative credit-risk models for retail and commercial portfolios. Build regulatory, capital, loss forecasting, valuation, and PPNR models using SAS and Python; analyze portfolio data; enhance modeling processes; address validation, audit, and regulatory findings; and collaborate with regulators, auditors, and technical stakeholders. Requires advanced statistical modeling, predictive analytics, banking risk expertise, and programming in Python, SQL, PySpark, and GCP.
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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.

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