Oct 15, 2019
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 prior to 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. 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. The Artificial Intelligence Model Development Center of Excellence (AI MD CoE) team is a data science team, responsible for developing and deploying machine learning and AI solutions for a number of domain areas such as fraud prevention, credit risk, experience personalization, customer listening, anomaly detection and operational cost 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 "Lead - Model Monitoring and Review" role would be responsible for executing on the model monitoring and model rapid refresh functions of the CoE. The role would create a standardized and efficient process for model monitoring so that risks around model degradation and failure are identified in a consistent and timely way. Also that the model retraining on a fresh set of data is performed in a speedy manner, but with the appropriate controls to ensure model robustness and stability. Additional responsibilities would include the quality review of model related technical documentation going to Model Risk Mgmt as well as other audit and regulatory bodies. A key requirement out of this role would be to make sure that industry best practices for model monitoring and refresh are appropriately brought into the processes followed by the AI Model Development CoE. This would include identification and selection of the potential external solutions that meet this overall requirement, as well as bringing in useful open source frameworks. The role of the Leader would be to hire and manage a team of data scientists and documentation review experts that can deliver on the objectives of the role. KEY RESPONSIBILITIES INCLUDE: Defining the operating framework for model monitoring - operations monitoring, drift monitoring, performance etc. Defining the framework for rapid refresh of models and operational approach. Undertaking the model monitoring and simple model refresh tasks, per the model monitoring and update framework (see above) and per the needs of specific models, defined by the Model Developer. Also identification of solutions to improve process efficiency through automation approaches, and implementing the same working closely with AI Enterprise Solutions and WF Technology. Working closely with Model Risk and other governance partners to ensure that the model refresh framework is implemented in a controlled manner, within the current policy framework. Define 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. Required Qualifications 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 in Artificial Intelligence, Natural Language Processing, Machine Learning, Distributed Computing, Chatbot, and Virtual Assistant 2+ years of Python experience Other Desired Qualifications Experience with building advanced statistical and machine learning models, in a banking or financial services context Experience with building NLP (Natural Language Processing) solutions in the financial industry Experience with monitoring or retraining advanced statistical and machine learning models Close familiarity with machine learning and statistical modeling techniques using open-source languages like Python or R Solid understanding of Model Risk Management requirements for banks and financial services companies Familiarity with Big Data technology for Data Management and Data Science Disclaimer 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.
Charlotte, NC, USA