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ALERT - To ensure we continue to fulfill our role as a provider of vital services to the public, we are still hiring and continue to recruit top talent to Wells Fargo. However, we have adjusted our hiring practices due to the COVID-19 situation and the related social distancing guidelines. As a result, throughout your application process, you may be asked to connect with us virtually. We encourage you to check our job postings regularly for updates and additions.

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Quantitative Analytics Specialist 3 - Data Science & AI/ML Research

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Job ID 5573329
Job Description

Important Note: During the application process, ensure your contact information (email and phone number) is up to date and upload your current resume when submitting your application for consideration. To participate in some selection activities you will need to respond to an invitation. The invitation can be sent by both email and text message.  In order to receive text message invitations, your profile must include a mobile phone number designated as “Personal Cell” or “Cellular” in the contact information of your application.

At Wells Fargo, we are looking for talented people who will put our customers at the center of everything we do. We are seeking candidates who embrace diversity, equity and inclusion in a workplace where everyone feels valued and inspired.

Help us build a better Wells Fargo. It all begins with outstanding talent. It all begins with you.

As the company's second line of defense, Corporate Risk — or Independent Risk Management — provides independent oversight of risk-taking activities. Independent Risk Management establishes and maintains Wells Fargo's risk management program and provides oversight, including challenges to and independent assessment of, the frontline's execution of its risk management responsibilities. We manage risk according to the  Risk Management Framework and ensure all employees understand their individual accountability for managing risk.

Model Risk is responsible for independently overseeing the management of model risk exposures (including monitoring design or coding errors and appropriate model usage) and the quality of model risk management practices across the company. This oversight extends throughout the end-to-end model lifecycle including model identification, risk ranking, development, validation, implementation, usage, and monitoring.
Model Risk at Wells Fargo places a strong emphasis in thought leadership and has pioneered the usage of Machine Learning and AI techniques to assess all aspects of model risk: data quality and bias, replication development models, assessing their assumptions and limitations, and developing benchmark models to challenge performance, interpretability, contributing a substantial amount of novel techniques to the field. You can see some of our latest papers in Arxiv.

Job Description

Working at the intersection of Data Science & AI/ML Research, Technology, and Quantitative Modeling, you will be contributing to the development of Wells Fargo’s next generation model diagnosis and validation system, a large scale distributed system able to conduct telediagnosis, telemonitoring, and adversarial testing of models distributed across the firm – with particular emphasis on AI/ML models.  This capability will be the key to scaling up and increasing the frequency of our model validation operations.  

You will be operating in a fast-paced skunkworks environment, focused on conducting end-to-end concept design and building functionally complete prototypes, with the objective of not just proving feasibility, but also resolve uncertainty around key design decisions, and produce complete specifications for implementation by internal technology teams, external vendors, and the open source community. 

Required Qualifications

  • 2+ years of experience in an advanced scientific or mathematical field
  • A master's degree or higher in a quantitative field such as mathematics, statistics, engineering, physics, economics, or computer science

Other Desired Qualifications
  • PhD or equivalent in computer science, electrical engineering, data science, or related areas
  • 4+ years of hands-on experience and deep knowledge in engineering data- and compute-intensive systems with a track record of success in delivering systems into production
  • Systems mindset, with the ability to abstract interfaces, future-proof designs, and anticipate potential problems, as well a keen ability to think in terms of building blocks, spot improvement opportunities and identify creative ways to find innovative solutions for them by remixing prior art in the AI/ML literature
  • Broad knowledge of common machine learning frameworks, with emphasis on big picture understanding of their internals, key abstractions used, and underlying design decisions, e.g. scikit-learn, pycaret, MLR, h2o, MLlib, MLJ, linfa, MLpack, tensorflow, pytorch.  Knowledge of AutoML systems (datarobot,  driverless AI, teapot) a big plus.
  • In depth knowledge of data science processes and everything that goes into building, testing, and operating a model end-to-end. Knowledge of recent frameworks for Machine Learning pipelines such as MLFlow, Kubeflow, Airflow, and TFX is a big plus
  • Broad knowledge of recent developments in AI/ML interpretability, safety, fairness, causality, and adversarial testing, with emphasis on frameworks (e.g. IBM Fairness 360 , IBM Adversarial Robustness Toolbox, IBM AI Explainability 360,  IBM Causal Inference 360, DoWhy, CausalML)
  • Knowledge of distributed computing frameworks (e.g. Spark, Dask, Ray), with deep subject matter expertise in at least one of them
  • Excellent programming skills in one systems language (e.g. C, C++, Java, Scala, OCaml, Rust, Go), and one specialized language (Python, R, Julia)
  • Excellent understanding of service-oriented architectures, microservices, modern RPC (e.g. gRPC) and messaging (e.g. Redis, Kafka, RabbitMQ)
  • Deep understanding of data modeling and relational databases.  Advanced SQL, including analytical functions and recent additions to the SQL standard.
  • Knowledge of common frameworks for analytical applications (e.g. R/Shiny, Dash, H2O Wave) highly desired -- especially  H2O Wave
  • Good verbal and written communication skills, as well as interpersonal skills, with the ability to conceptualize and communicate designs and plans, develop partnerships and collaborate with other business and functional areas

Street Address

NC-Charlotte: 401 S Tryon St - Charlotte, NC


All offers for employment with Wells Fargo are contingent upon the candidate having successfully completed a criminal background check. Wells Fargo will consider qualified candidates with criminal histories in a manner consistent with the requirements of applicable local, state and Federal law, including Section 19 of the Federal Deposit Insurance Act.

Relevant military experience is considered for veterans and transitioning service men and women.

Wells Fargo is an Affirmative Action and Equal Opportunity Employer, Minority/Female/Disabled/Veteran/Gender Identity/Sexual Orientation.

Benefits Summary


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