About Wells Fargo

Wells Fargo & Company (NYSE: WFC) is a leading global financial services company headquartered in San Francisco (United States). Wells Fargo has offices in over 20 countries and territories. Our business outside of the U.S. mostly focuses on providing banking services for large corporate, government and financial institution clients. We have worldwide expertise and services to help our customers improve earnings, manage risk, and develop opportunities in the global marketplace. Our global reach offers many opportunities for you to develop a career with Wells Fargo. Join our diverse and inclusive team where you will feel valued and inspired to contribute your unique skills and experience. We are looking for talented people who will put our customers at the center of everything we do. Help us build a better Wells Fargo. It all begins with outstanding talent. It all begins with you.

Market Job Description

About Wells Fargo in India & Philippines Wells Fargo in India & Philippines enables global talent capabilities for Wells Fargo Bank NA., by supporting business lines and staff functions across Technology, Operations, Risk, Audit, Process Excellence, Automation and Product, Analytics and Modeling. We are operating in Hyderabad, Bengaluru, Chennai & Manila locations. Department Overview

The Wealth Management Data Solutions (WM DS) organization is an integrated product owner structure within Wealth Investment Management (WIM) providing quantitative modelling support, direct technology services, as well as data products and data analytics to WIM. With 300+ staff members across the US and India, Data Solutions is on a mission to modernize its technology and build stronger, more agile scrum teams. We are seeking world-class talent, like you, to help deliver innovative solutions and to drive that transformation. If you’re passionate about tackling complex challenges and advancing technology, we invite you to join us in shaping the future of data-driven solutions.

 Team Overview – Retail Investing and Financial Advice modelling team

The Retail Investing and Financial Advice Modeling (RIFAM) team is a front-line model development team tasked to provide quantitative support to the Wealth Investment Management (WIM) business, in accordance with Wells Fargo model life cycle policies and procedures. The team has members across the US and India and spans a portfolio of complex models across the Investment Solutions and Advice and Advice & Planning Centers of Excellence.

RIFAM is now expanding to explore applications of machine learning (ML) and generative AI (GenAI) in the wealth investment management space.

About the Role

Wells Fargo is looking for Quantitative Analytics Specialist.

The ideal candidate will have prior experience in both traditional quantitative modeling in the space of wealth management, as well as familiarity in the areas of machine learning and Generative AI.

RIFAM is looking for a professional with hands-on experience with the development, documentation and validation of quantitative models in the wealth investment and financial planning space, with a strong background in modeling techniques and an appreciation for various modeling approaches. The successful candidate should have a solid understanding of quantitative models in the risk neutral “Q” and historical “P” risk measures and areas of finance (“P” side preferred), portfolio optimization, factor models, forecasting models and Monte Carlo simulations. Solid understanding of statistical concepts as they relate to finance is highly desirable.

In addition, the candidate should demonstrate prior experience with machine learning and generative AI models to help assess the potential business impact of proprietary or vendor capabilities being evaluated in the WIM business. The ideal candidate will drive comparative analyses of different GenAI solutions, evaluate their performance and establish proof of value to guide business decision and adoption.

The role will be interacting with a broad variety of partners, from portfolio managers and investment strategists in the business to model validators, fiduciary investment risk, auditors, and technology partners. Candidates should be comfortable with explaining technical concepts to both technical and non-technical audiences.

Responsibilities

Support complex initiatives including creation, implementation, documentation and performance monitoring of complex quantitative models using statistical, financial and other methods.
Support the model life cycle, including inception, development, and model maintenance according to the model risk management policy.
Establish proof of value of several ML and GenAI vendor-based solutions to be deployed in the WIM business.
Provide solutions to business needs and ad-hoc analyses to support modeling decisions or help in the business decision making process.
Support the creation of benchmarks and provide proper developmental evidence for the supported models.
Design model performance metrics, seeking the support from the business and presenting decisions to our risk partners.
Actively participate in the documentation and submission of our models to independent risk partners and provide necessary support to address concerns.
Review and assess models inclusive of technical, audit, and market perspectives.
Present results of analysis to businesses, risk partners, regulators and auditors.

Required skills:

2+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Master's degree or higher in statistics, mathematics, physics, engineering, computer science, economics, or quantitative discipline

Desired Skills :

7+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education.
Master's degree or higher in statistics, mathematics, physics, engineering, computer science or quantitative discipline

Master’s degree in a quantitative discipline
Chartered Financial Analyst (CFA) holder.
Model development and implementation experience in the Wealth and Investment Management and/or Financial Planning industry.
Experience with evaluation of Large Language Models (LLMs) models, bias detection, and evaluation methods (perplexity, coherence, hallucination detection).
Ability to benchmark GenAI/ML models against industry standards and best practices.
Understanding of financial regulations related to AI and chatbot use in investment management.
Experience in quantitative analysis and modeling of financial products
Experience with portfolio optimization, factor models and Monte Carlo simulations techniques
Prior experience with capital market assumptions modeling, including factor modeling and forecasting highly desirable.
Solid understanding of statistics and time series analysis.
Experience with model review, model validation and model lifecycle
Working experience developing or benchmarking models in Python
Proficiency with SQL.
Experience with GitHub desirable.
Track record of quality and timely delivery of work products
Comfortable addressing ambiguity, conflicting requirements
Track record of taking initiative and accountability
Ability to communicate advanced quantitative concepts clearly to both technical and non-technical audiences.
Willingness to adapt in a fast-paced work environment; strong sense of urgency
Excellent verbal, written, and interpersonal communication skills
Ability to develop partnerships and collaborate with other business and functional areas

Posting End Date:

29 Apr 2025

*Job posting may come down early due to volume of applicants.

We Value Diversity

At Wells Fargo, we believe in diversity, equity and inclusion in the workplace; accordingly, we welcome applications for employment from all qualified candidates, regardless of race, color, gender, national origin, religion, age, sexual orientation, gender identity, gender expression, genetic information, individuals with disabilities, pregnancy, marital status, status as a protected veteran or any other status protected by applicable law.

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 US: 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.

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.