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.

This role is a part of DMI's Enterprise Analytics and Data Science Team – the central analytics group tasked with solving high-impact business challenges and standing up cutting-edge analytical capabilities to be shared across Wells Fargo's analytic community.
 
The Natural Language Processing (NLP) Data Engineer will be responsible for developing production-grade, reusable, scalable, and well-architected data pipeline to allow for NLP model development, enable model deployment, and accelerate AI speed-to-market.

As an active member of Agile Pod, the candidate will be actively involved in model development workflow and work with other NLP team to generate innovative ideas around simplification and improvisation of model development. He/she will be a key player in ensuring that the data pipeline is tested, evaluated/validated, and well-architected to allow for model development and seamless integration with other system layers in a production environment. He/she needs to be hands-on in creating data pipeline libraries using Python and/or Scala programming languages and have keen interest in understanding and applying big data frameworks such as Spark, Hadoop, etc. and data science approaches such as deep learning neural nets for Natural Language Processing model development.
 
Key Responsibilities:

• Complete data exploration analysis to ensure pre and post ingested datasets are accurate and complete for AI model development.
• Design, develop, and deliver production-grade, reusable, scalable, and well-architected NLP data pipeline solutions using Python and/or Scala programming languages.
• Perform end-to-end data pipeline testing by consistently measuring solution delivery against AI model development best practices and standards for performance efficiency, flexibility, and optimization.    
• Adapt and/or refine AI model development best practices and standards for continuous improvement of data pipeline development.
• Partner with AI Technology team to refactor data pipeline code, to prepare and handoff model artifacts for successful operationalization of model.  
• Help advance natural language processing (NLP) capabilities by proofing several modern tools and technologies as required.

• 8+ years of experience in one or a combination of the following: reporting, analytics, or modeling demonstrated through work or military experience; or a Masters degree or higher in a quantitative field such as applied math, statistics, engineering, physics, accounting, finance, economics, econometrics, computer sciences, or business/social and behavioral sciences with a quantitative emphasis and 5+ years of experience in one or a combination of the following: reporting, analytics, or modeling
• 1+ years of Apache Spark design and development experience using Scala, Java, Python or Data Frames with Resilient Distributed Datasets (RDDs)
• 5+ years of SQL experience
• 3+ years of experience with Big Data or Hadoop tools such as Spark, Hive, Kafka and Map
• 2+ years of experience with data manipulation, cleansing, and transformation
• 3+ years of Python experience

• Extensive knowledge and understanding of research and analysis
• Strong analytical skills with high attention to detail and accuracy
• Excellent verbal, written, and interpersonal communication skills
• 1+ years of Natural Language Processing (NLP) experience

• Experience working with unstructured data and/or text analytics is a plus
• Experience working with Data Scientist teams for developing data pipelines
   

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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.