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Wells Fargo
CHARLOTTE, North Carolina, United States
(on-site)
Posted
1 day ago
Wells Fargo
CHARLOTTE, North Carolina, United States
(on-site)
Job Type
Full-Time
Job Function
Other Profession
Quantitative Analytics Specialist (#001887)
The insights provided are generated by AI and may contain inaccuracies. Please independently verify any critical information before relying on it.
Quantitative Analytics Specialist (#001887)
The insights provided are generated by AI and may contain inaccuracies. Please independently verify any critical information before relying on it.
Description
At Wells Fargo, we want to satisfy our customers' financial needs and help them succeed financially. We're 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.
Wells Fargo Bank N.A. seeks a Quantitative Analytics Specialist in Charlotte, NC.
Job Role and Responsibility:
Be involved in the development of state-of-the-art methods in quantitative modeling using statistical and machine learning (ML) techniques and implementing them in efficient/scalable algorithms. Identify cutting-edge techniques in academia and industry as well as implementing them for applications in risk management. Drive the development of methodology and algorithms by conducting applied research. Disseminate best practice across the quantitative modeling community within the bank. Develop model library to support validation process. Design benchmark models and implement and automate their use within our advanced computing platform. Collaborate with internal and external quantitative communities to keep abreast of latest developments and practices in quantitative risk. Facilitate credible challenge of the processes/models and to develop the skills of the validation team. Be capable of building collaborative working environments including leading process improvement projects. Develop, implement, and calibrate various analytical models. Perform highly complex activities related to financial products, business analysis and modeling. Build basic statistical and mathematical models using Python, R, C++ and SQL. Perform analytical support and provide insights regarding a wide array of business initiatives. Provide solutions to business needs and analyze workflow processes to make recommendations for process improvement in risk management. Telecommuting is permitted up to 2 days a week. Position must appear in person to the location listed as the work address.
Travel required: 0%
Required Qualifications:
Degree required: Master's degree in Finance, Econometrics, or a related discipline.
Amount and type of experience required: 2 years of experience in the job offered or in a related quantitative analytics role. Experience can be gained concurrently with graduate level coursework.
Specific skills required:
Specific skills required: Skills can be gained through work experience or graduate level coursework. Experience in modeling (statistical and machine learning), optimization, algorithm development, programming, and coding including Generalized Linear Models, Gradient Boosting Machines, or Random Forrests, the related training and optimization algorithms, and their common implementations in R and/or Python; In-depth knowledge of Machine Learning/Deep Learning algorithms and their implementation such as XGBoost or LightGBM as well as Neural Networks, including Multilayer Perceptrons or Convolutional Neural Networks; Strong computing and programming background and knowledge of one or more languages including Python, Java, or R; Experience with Machine Leaning/Artificial Intelligence computing platforms and tools TensorFlow and Keras; Experience with Graphics Processing Unit (GPU) programming, multi-core, or distributed programming; Ability to work with large datasets and experience in database management and tools such as Hadoop, Spark or SQL.
Posting End Date:
25 Aug 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.
Job ID: 85536983
Please refer to the company's website or job descriptions to learn more about them.
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