Wells Fargo

Job Category:

Information Technology

Location:

West Des Moines, Iowa

Country:

United States

Postal Code:

50061

Approximate Salary:

Not Specified

Position Type:

Full Time

Phone:

415) 820-7800

Analytic Consultant 5 - Senior Data Scientist

Wells Fargo - West Des Moines, Iowa

Posted: 09/6/2018

Job Description

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.

Corporate Risk helps all Wells Fargo businesses identify and manage risk. We focus on three key risk areas: credit risk, operational risk, and market risk. We help our management and Board of Directors identify and monitor risks that may affect multiple lines of business, and take appropriate action when business activities exceed the risk tolerance of the company.

As a Senior Data Scientist in Wells Fargo Home Lending’s conduct risk analytics team under Real Estate Compliance and Operational Risk (RECOR), you will be responsible for recognizing opportunities to improve the prediction of misconduct through the use of Machine Learning (ML) and Natural Language Processing (NLP) techniques. More specifically, you will build models that evaluate and improve new compliance regulations implemented by the Feds, CFPB, and OCC by combining both unstructured data, using text analytics and Natural Language Processing (NLP), and structured data.

This Analytic Consultant 5 - Senior Date Scientist will also serve as a mentor to other team members by advising in the areas of AI/ML, and will represent the RECOR team in partnership with the enterprise AI/ML teams to deliver enterprise class solutions.

Key Responsibilities Include:

  • Translate and summarize complex analysis into understandable, actionable insights and recommendations that directly drive effective business strategy
  • Think creatively to identify opportunities to leverage machine learning in order to improve the identification of new compliance regulations violations implemented by the Feds, CFPB, and OCC
  • Utilize text mining, data munging, data preparation, and other advanced analytical techniques to collect, explore, and extract insights from both structured and unstructured/text data
  • Develop machine learning and other AI models with Python or R
  • Use a combination of Natural Language Processing techniques and other modeling techniques to extract useful information from both unstructured and structured data
  • Scale analytics solutions to Big Data with Hadoop, Spark/PySpark, and other Big Data tools
  • Take initiatives and drive each project to completion with minimal guidance, while effectively managing multiple projects at a time
  • Mentor other team members and collaborate with the Enterprise Data Science teams

** Preferred Locations are West Des Moines, IA or Saint Louis Park, MN; however other locations within the Wells Fargo footprint may be considered**

Required Qualifications

  • 8+ years of experience in one or a combination of the following: reporting, analytics, or modeling; 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+ year of Python experience
  • 2 + years of text analytics experience
  • 2+ years of experience with machine learning model development
Desired Qualifications

  • 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+ year of real estate lending experience
  • Ability to develop partnerships and collaborate with other business and functional areas
Other Desired Qualifications
  • Experience with TensorFlow
  • 3+ years of SQL experience
  • 3+ years of Python experience
  • 3+ years of experience with Predictive modeling using Machine Learning algorithms such as Random Forests, Na ve Bayes, Neural Networks, MaxEnt, SVM, Topic Modeling/LDA, Ensemble Modeling, GB, etc.
  • 3+ years of experience with Natural Language Processing (NLP) using common NLP techniques such as tokenization/ngrams, part-of-speech tagging (POSTagger), parsing, stemming
  • Experience with semantic analysis (named entity recognition, sentiment analysis)
  • Experience with modeling and word representations (TF-IDF, LDA, word2vec, doc2vec)
  • Experience working with big data infrastructure and tools such as Hive and Spark
  • Experience reading, understanding, and implementing algorithms and other techniques from industry and academic publications
Job Expectations

  • This position requires compliance with all mortgage regulatory requirements and Wells Fargo's compliance policies related to these requirements including acceptable background check investigation results. Successful candidates must also meet ongoing regulatory requirements including additional screening and required reporting of certain incidents.
  • Ability to travel up to 15% of the time
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.

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