Senior Quantitative Analytics Specialist - Innovation and Analytics
141753-NC-Three Wells Fargo Center, Charlotte, United States
⚠️ We'll shut down after Aug 1st - try foo🦍 for all jobs in tech ⚠️
Full Time Senior-level / Expert USD 111K - 217K
Wells Fargo
Committed to the financial health of our customers and communities. Explore bank accounts, loans, mortgages, investing, credit cards & banking services»About this role:
Wells Fargo is seeking a Senior Quantitative Analytics Specialist (SQAS) on our internal audit innovation team. In this role you will play a crucial role in the development and maintenance of our data science and business intelligence solutions. This role will specialize in assisting with machine learning, deep learning, and generative AI initiatives that will be utilized by internal audit leaders to enhance and expedite decision-making and drive automation. You will provide expertise within and across business teams, demonstrate the ability to work independently, and apply problem-solving skills to resolve complex issues.
We’re seeking a highly technical individual contributor who is adept at advanced AI/ML algorithms and their applications in financial institutions to join our AI/ML Center of Excellence in Internal Audit. The individual must have a strong data science / computer engineering background and must be skilled in designing and deploying Machine Learning models using Python based frameworks. The team plays a critical role in providing internal audit with Artificial Intelligence Models across various business areas, such as Fraud, Credit Risk and Bank Operations.
Lead and participate in defining and transforming data science solution requirements into quantifiable solutions.
Independently carry out tasks, using critical thinking and problem-solving skills to devise effective solutions.
Design, train, and deploy supervised and unsupervised machine learning and deep learning models in a Unix based GPU environment using python (pytorch, transformers, BertTopic, unsloth, langgraph, langchain, etc..) to drive scalable solution development.
Develop and advise on Large Language Model (LLM) solutions including RAG, and SFT.
Extensive knowledge of github operations for project versioning, code development, and project management.
Write clean, well-commented code for easy collaboration and maintain structured project documentation using GitHub and/or Jira.
Technical model documentation experience (Model development documentation)
In this role, you will:
Perform highly complex activities related to creation, implementation, and documentation
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 structured securities and provide expertise on theory and mathematics behind the data
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
Required Qualifications:
4+ 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 a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science
Desired Qualifications:
Proven ability to Identify opportunities to integrate traditional ML techniques when appropriate and ensure a strong data science foundation is present in AI applications.
Strong statistical modeling or computer science background and hands on model development or validation skills
Considerable knowledge of machine learning algorithms and their applications, including Random Forest, GBM, XGBoost, deep learning, NLP, computer vision, LLMs.
Experience with building complex deep learning architectures such as MLPs, RNNs, CNNs and Generative AI frameworks such as RAG and Agentic AI.
Extensive experience with Deep Learning and LLM frameworks such as PySpark, SparkML, PyTorch, Tensorflow/Keras, MXNet, LangChain , Llamaindex
Experience in Load Balancing, GPU based processing, Performance Optimization
Knowledge of financial industry general model development lifecycle is preferred but not required
Prior experience working with Model Risk Management
Demonstrated independence, teamwork and leadership skills
Strong project management skills
Excellent written and verbal communication skills
Job Expectations:
Hybrid work schedule
This position is not eligible for Visa sponsorship
Pay Range
Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to achievements, skills, experience, or work location. The range listed is just one component of the compensation package offered to candidates.
$111,100.00 - $217,200.00Benefits
Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below. Visit Benefits - Wells Fargo Jobs for an overview of the following benefit plans and programs offered to employees.
- Health benefits
- 401(k) Plan
- Paid time off
- Disability benefits
- Life insurance, critical illness insurance, and accident insurance
- Parental leave
- Critical caregiving leave
- Discounts and savings
- Commuter benefits
- Tuition reimbursement
- Scholarships for dependent children
- Adoption reimbursement
Posting End Date:
7 Aug 2025*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.
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.
Tags: Architecture Business Intelligence Computer Science Computer Vision Credit risk Deep Learning Economics Engineering Generative AI GitHub GPU Jira Keras LangChain LLMs Machine Learning Mathematics ML models MXNet NLP Physics PySpark Python PyTorch RAG SparkML Statistical modeling Statistics TensorFlow Transformers XGBoost
Perks/benefits: Career development Health care Insurance Medical leave Parental leave Team events
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