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 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. Join our diverse and inclusive team where you'll feel valued and inspired to contribute your unique skills and experience.

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

DIVISIONAL INFORMATION
Data Management and Insights (DMI) is transforming the way that Wells Fargo uses and manages data. Our work enables Wells Fargo to empower and inform our team members, deliver exceptional experiences for our customers, and meet the elevated expectations of our regulators. The team is responsible for designing the future data environment, defining data governance and oversight, and partnering with technology to operate the data infrastructure for the company. This team also provides next generation analytic insights to drive business strategies and help meet our commitment to satisfy our customers' financial needs.

***CANDIDATES MUST SIT ONSITE 4-5 DAYS PER WEEK IN ONE OF THE CORE DMI HUB LOCATIONS LISTED TO BE CONSIDERED (POST COVID 19)***

The Artificial Intelligence Model Development Center of Excellence (AI MD CoE) is a data science team, responsible for developing and deploying machine learning, NLP, and AI solutions for a number of domain areas such as fraud prevention, credit risk, experience personalization, customer listening, risk and compliance, anomaly detection and operational improvement. The CoE partners closely with the AI Enterprise Solutions and the AI Technology teams at the bank, and brings a cross-functional approach to identifying, developing and deploying AI solutions. The CoE requires high-skill/ high-motivation individuals who enjoy working collaboratively in a team setting, used to taking decisions autonomously and comfortable with a dynamic work environment.

The NLP Data Science team in the AI MD CoE is responsible for developing and deploying NLP, machine learning, and AI solutions for key strategic Enterprise initiatives such as customer experience improvement, risk management and compliance, business operational excellence, and team member experience that leverage unstructured data. The team is looking for an experienced leader to lead its NLP model development shared services team.

This leader would be responsible for managing a team of highly skilled data scientists to design, develop, and implement AI/ML models as well as building foundational capabilities in areas of annotation and model development pipelines. Under your leadership, the team will leverage unstructured data such as emails, text messages, notes, voice data, and semi-structured data in combination of structured data to build NLP Machine Learning/Deep Learning models using open stack languages (mainly Python/PySpark/PyTorch). In addition, you are responsible of building and enhancing foundational data science capabilities such as model experimental workflow, model development pipeline, plug and play modules to institutionalize reusable, at scale modules to accelerate AI model development. You will own and expand the community developed workflow framework, pipeline, packages, libraries, etc. and make them operable to the COE data scientists.   You will also be charged with setting up standard annotation practices and integrating annotation in an active learning framework. You will be responsible for relationship management with LOB business functional executives to frame the problem, select the right AI approach, resources, and tools to meet business requirements. Collaborating with WF AI Tech, AI business, and LOB leads, you and your team will develop, deliver, and deploy AI/ML models on the Wells Fargo AI open source platform, scale them up, and operationalize them for business use. You and your team expect to follow and contribute to the Model Development Life Cycle that focuses on generating standardized processes, repeatable modules, and required artifacts to scale up model development, model review, and validation. You will work with Wells Fargo model risk governance and validation teams to ensure the modeling processes and procedures meet corporate model risk policy and requirements. You will also be managing work efforts with AI vendors to ensure vendor AI models pass Wells Fargo model risk policies and requirements including model development documents and reviews.

KEY RESPONSIBILITIES INCLUDE:

• Lead a team of highly skilled data scientists to design, develop, and deploy AI/ML models using state of the art techniques available in the open stack (Python/PySpark/PyTorch) and/or vendor solutions
• Build and enhance foundational capabilities such as workflow processes, model pipeline, reusable and plug and play modules and other community developed products
• Establish annotation best practices and integrate annotation to an active learning framework
• Partner with LOB business executives to frame the problem, manage the model development process, and business relationship
• Manage a portfolio of the data science projects including the following responsibilities:
  • Finalize project scope
  • On-going touch-base with business partners and governance stakeholders
  • Define priorities in partnership with the business partners during on-going development
  • Ensure project quality and delivery timelines
• Adhere to corporate model risk policy and ensure compliance with model risk management
• Working with other data science teams to identify, gather, retain, and publicize modeling artifacts required for approved and repeatable processes
• Work with AI technology and production teams to operationalize models
• Review vendor models and solutions and/or models developed outside of AI MD CoE
• Work effectively in a collaborative environment with agile project management methodologies for data science
• Provide technical advice to other members of the team and across the organization on topics including machine learning algorithms, hyper-parameter tuning/search, and traversing across multiple big data platforms
• Identify and lead the evaluation of new software techniques and technologies, including delivery of results
• Identify new applications for machine learning across the company and work with business partners to pilot
• Adhere to and implement a documentation and artifact review process for model documentation and artifacts, created as part of the model development work performed by model development teams
• People management responsibilities such as hiring, performance management, routine travel and equipment/ software related approvals

As a Team Member Manager, you are expected to achieve success by leading yourself, your team, and the business. Specifically you will:

• Lead your team with integrity and create an environment where your team members feel included, valued, and supported to do work that energizes them.
• Accomplish management responsibilities which include sourcing and hiring talented team members, providing ongoing coaching and feedback, recognizing and developing team members, identifying and managing risks, and completing daily management tasks.

• 4+ years of experience in an advanced scientific or mathematical field
• 2+ years of leadership experience
• A master's degree or higher in a quantitative field such as mathematics, statistics, engineering, physics, economics, or computer science
• 2 + years of experience using quantitative machine learning techniques
• 2+ years of Natural Language Processing (NLP) experience
• 2+ years of Python experience
• 4+ years of statistical modeling experience
• 2+ years of leadership experience including coaching, training, and mentoring Data Scientists

• Hands on familiarity with machine learning and statistical modeling techniques using open-source languages like Python, PySpark, PyTorch
• Software development experience
• Solid understanding of Model Risk Management requirements for banks and financial services companies. Able to de-mystify AI models
• Experience building AI solutions that have been implemented/productionalized
• Hands on experience with deep learning toolkits such as Tensorflow, Keras, PyTorch, Dynet
• Hands on experience writing data processing and data pipeline for unstructured data model development including gathering and building datasets to collect intents, cleaning messy data, designing feedback loop on data needs
• Experience building intent recognition and classification models. Experience with phrase level identification.
• Hands on experience with BERT, ELMO, CRF models.
• Hands on experience with data labeling design for intent classification
• Experience with active learning and reinforcement learning

NC-Charlotte: 11625 N Community House Road - Charlotte, NC
MN-Minneapolis: 600 S 4th St - Minneapolis, MN
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GA-Atlanta: 3579 Atlanta Ave - Atlanta, GA
CA-SF-Financial District: 333 Market St - San Francisco, CA

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.