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.
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) is a data science tea, 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, are used to making decisions autonomously, and are 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 AI model professional to add to its NLP model development team.
In this Quantitative Analytics Specialist 3 role you will be responsible for designing, developing, and implementing AI/ML models to support various initiatives across the enterprise. You 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). You will collaborate with LOB organizations to frame the problem, and explore various modeling methodologies and tools to deliver business solutions according to timelines. Collaborating with WF AI Tech, AI business, and LOB leads, you 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 are 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 ensure the modeling processes and procedures meet corporate model risk policy and requirements. You will also be working 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:
As part of the NLP data science team, you will work within the team to follow and develop AI solutions according to the MDLC process:
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
Partner with LOB leads to frame the problem, explore various ML/DL model architectures and methodologies, generate required artifacts related to model development life cycle (MDLC), author the model development document, and deliver AI models that meet business needs
Adhere to corporate model risk policy and ensure compliance with model risk management
Work 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
Work effectively in agile project management methodologies for data science
Share knowledge with 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
Contribute to NLP data science team's group effort to stay current with the cutting edge NLP/ML/DL algorithms, methodologies in the open source community, and vendor solutions.
2+ years of Python experience
2 + years of experience using quantitative machine learning techniques
2+ years of Natural Language Processing (NLP) 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 an advanced scientific or mathematical field
Other Desired Qualifications
Hands on familiarity with machine learning and statistical modeling techniques using open-source languages like Python, PySpark, PyTorch
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, and 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
Experience with AI model transparency and explainability studies
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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.
Internal Number: 5549424-10
About Wells Fargo
Wells Fargo & Company (NYSE: WFC) is a diversified, community-based financial services company with $1.9 trillion in assets. Wells Fargo’s vision is to satisfy our customers’ financial needs and help them succeed financially. Founded in 1852 and headquartered in San Francisco, Wells Fargo provides banking, investment and mortgage products and services, as well as consumer and commercial finance, through 7,400 locations, more than 13,000 ATMs, the internet (wellsfargo.com) and mobile banking, and has offices in 32 countries and territories to support customers who conduct business in the global economy. With approximately 260,000 team members, Wells Fargo serves one in three households in the United States. Wells Fargo & Company was ranked No. 29 on Fortune’s 2019 rankings of America’s largest corporations. News, insights and perspectives from Wells Fargo are also available at Wells Fargo Stories.
www.wellsfargo.com | Twitter: @WellsFargo