15 days old

Quantitative Analytics Specialist 3

Tempe, AZ 85281
  • Job Code
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 want to satisfy our customers financial needs and help them succeed financially. Were looking for talented people who will put our customers at the center of everything we do. Join our diverse and inclusive team where youll 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.

Enterprise Finance drives financial management for the company and maintains and enhances risk and financial controls. Key functions within Enterprise Finance include finance and accounting; Treasury; corporate development, mergers, and acquisitions; Data Management and Insights, the Customer Remediation Center of Excellence, Enterprise Shared Services, Business Process Management, and Corporate Strategy. Enterprise Finance informs shareholders, regulators, taxing authorities, team members, and leaders of the companys financial performance through earnings releases, investor meetings and conferences, and meetings with regulators and credit rating agencies, following appropriate reporting guidelines. They also maintain and enhance risk and financial controls and lead many of the companys shared services functions including corporate properties, security, and global services.

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 Natural Language Processing (NLP) Data Science team in the Artificial Intelligence Model Development Center of Excellence (AI MD CoE) team is a data science team, responsible for developing and deploying NLP, machine learning (ML), and AI solutions for the enterprise. They work on key strategic Enterprise initiatives such as customer experience improvement, risk management and compliance, business operational excellence, and team member experience. The team is looking for an experienced analytics professional to add to its NLP conversational AI (chatbot) model development team.

As part of the NLP data science team for chatbot model development, you will be responsible for researching, designing, developing, and implementing NLP models for conversational AI solutions across the enterprise and Wells Fargo lines of business. You will be leveraging unstructured text such as chats, emails, text messages, notes, voice data and semi-structured data in combination of structured data to build Chatbot models using deep learning and machine learning techniques. You will use open stack programming languages and/or vendor solutions to develop models and deploy them on Wells Fargos AI/chatbot platform. You will deliver and deploy AI/ML models on the Well Fargo AI open source platform to scale these solutions and embed them in the operational processes.

The ideal candidate should be able to research SOTA techniques for NLP and chatbot related advancement across industry and academia; quickly test and experiment with ideas and existing open source materials; and think outside the box to uncover new ways to analyze unstructured data in conjunction with analytical tools to answer complicated business questions. As part of the model development team, you will be responsible of delivering solutions that meet business needs as well as any efforts related to model documentation and reviews to ensure the modeling processes and procedures meet corporate model risk policies and requirements.


As part of the NLP data science team focusing on Conversational AI models across the enterprise, you will work within the team to follow and develop solutions according to our analytic process:

Partner with LOB business executives to frame the problem and define/identify business objectives
Identify/assess data sources
Research, and quickly experiment and implement working prototypes for testing new ideas
Design, develop, and deploy AI/ML/deep learning models using state of the art NLP and ML techniques available in the open stack and/or vendor solutions
Data visualization
Communication of results
Responsible for model development document and monitoring processes
Drive continuous process improvement, and increase the efficiency and quality of AI project deliveries
Adhere to corporate model risk policy and ensure compliance with model risk management policies
Working with other data science teams to identify, gather, retain, and publicize modeling artifacts required for approved and repeatable processes
Contribute to NLP data science teams group effort to stay concurrent with the cutting edge and bleeding edge of NLP/ML/DL algorithms, methodologies in the open source community and vendor solutions.
Work with AI technology and production teams to operationalize models
May be called upon to review vendor models and solutions and/or models developed outside of EADS

Required Qualifications

2+ years of experience in an advanced scientific or mathematical fieldA master's degree or higher in a quantitative field such as mathematics, statistics, engineering, physics, economics, or computer science2+ years of development experience with languages such as Python, Java, Scala, or R

Desired Qualifications

Knowledge and understanding of Machine Learning, Deep Learning, Linear Regression, Models (Tensor Flow)A PhD in a quantitative discipline Strong analytical skills with high attention to detail and accuracyAbility to work and influence successfully within a matrix environment and build effective business partnerships with all levels of team members2+ years of experience in Artificial Intelligence, Natural Language Processing, Machine Learning, Distributed Computing, Chatbot, and Virtual Assistant

Other Desired Qualifications

Experience in one or a combination of the following: computer science, computational linguistics, engineering, analytics, or statistical modeling, and/or research in the area
Experience of machine learning and deep learning models and frameworks
Knowledge of libraries like scikit-learn, keras, Tensorflow 2.0, PyTorch
Knowledge of advanced NLP technologies like transformers, attention, BERT, ELMO
Experience building virtual assistants using Dialog flow, Microsoft Bot Framework, Rasa or in any popular Bot Building frameworks; Knowledge on IVR based application platforms and Conversational IVR
Hands on experience writing data processing and data pipeline for Chatbot 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 data labeling design for intent classification
Experience with model governance requirements. Able to de-mystify AI models to make them transparent and explainable
Knowledge and/or experience with the following:
Implementing solutions with common NLP frameworks and libraries in Python (NLTK, spaCy, genism, keras, pytorch, TF) or Java (Stanford CoreNLP, NLP4J)
Common NLP techniques, such as
oPre-processing (tokenization, part-of-speech tagging, parsing, stemming)
oSemantic analysis (named entity recognition, sentiment analysis)
oModeling and word representations (TF-IDF, LSA, LDA, word2vec, ELMO)
oExperience with GPT2, Transformer-XL, XLNet, RoBERTa, XLM and other community models
Data engineering skills (deploying analytical solutions across an organization in a production format)
Experience using GitHub for version control and collaboration; developing python libraries to streamline pipelines
Knowledge of Computer Science fundamentals in data structures, algorithm design, problem solving and complexity, scalability analysis
Experience with active learning and reinforcement learning
Experience with an object oriented language like Java
Knowledge of libraries like S4TF a plus

Street Address

NC-Charlotte: 401 S Tryon St - Charlotte, NCMN-Minneapolis: 600 S 4th St - Minneapolis, MNNC-Charlotte: 11625 N Community House Road - Charlotte, NCAZ-Tempe: 1150 W Washington St - Tempe, AZIA-Des Moines: 6200 Park Ave - Des Moines, IAIA-Des Moines: 800 Walnut St - Des Moines, IAMN-Minneapolis: 255 2nd Ave S - Minneapolis, MNCA-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.



Posted: 2020-02-05 Expires: 2020-03-06

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Quantitative Analytics Specialist 3

Wells Fargo
Tempe, AZ 85281

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