1+ months

Data Scientist (Analytic Consultant 5)

Minneapolis, MN
  • Job Code
Job Description

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.

Job description

This role is a part of DMIs Enterprise Analytics Team the central analytics group tasked with solving high-impact business challenges and standing up cutting-edge analytical capabilities to be shared across Wells Fargos analytic community.

We are looking for a high performer to join our team and help us solve challenging and interesting business problems through rigorous data analysis and predictive modeling. In this highly technical role, you will support Customer Genome program - the initiative focused on creating analytically derived insights to inform development of personalized customer experience and marketing programs. As part of the core Customer Genome team, you will collaborate with other data scientists, data engineers, and domain experts to design, automate, and deploy generation of business insights based on predictive models and machine learning algorithms.

Key Responsibilities Include:

  • Conduct exploratory data analysis, mine data (e.g., clustering), and prepare modeling datasets from multiple data sources. Build and implement predictive models using machine learning algorithms (e.g., neural networks, SVM, Na ve Bayes classifier), as well as traditional statistical modeling techniques (e.g., linear and logistic regression).
  • Design and build large scale systems of various complexities by implementing and operationalizing supervised and unsupervised machine learning (ML) algorithms through reduction of computational complexity and algorithm optimization.
  • Improve existing ML systems; provide on-going support, maintenance, and enhancements of the implemented algorithms.
  • Collaborate with data engineers and work with complex databases to help optimize data retrieval processes to support ML algorithm automation.
  • Utilize emerging analytical and programming techniques to explore internal and external unstructured and semi-structured data; recommend how these additional data sources can be used to enhance existing data and provide additional insight.

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
  • 3 + years of experience using quantitative machine learning techniques
  • 2+ years of design, implementation and governance experience with Artificial Intelligence, Natural Language Processing or Machine Learning architecture
  • 2+ years of Big Data experience

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

Other Desired Qualifications
  • 2+ years of experience working with big data infrastructure and tools (e.g., Hadoop, Spark, H2O, Java, Kafka)
  • Advanced degree in technical field (e.g., Computer Science, Machine Learning, Software Engineering, Electrical Engineering)
  • Strong programming skills using tools like R, Python, SQL, Hive with ability to manipulate data for analytical purposes and to code efficient algorithms with scalability. Ability to learn new technologies quickly
  • Knowledge of statistical methods (e.g., probability, multivariate data analysis, regression, PCA, time-series analysis) and experience with machine learning techniques, such as neural networks, decision trees, random forests, SVM, GBM, ensemble learning, etc
  • Solid foundation in data structures, computer arithmetic, algorithms, computability and complexity, computer architecture, and system design; experience with designing and deploying large scale production ML algorithms on GPU, CPU, distributed systems
  • Exceptional analytical, programming, critical thinking, and problem-solving skills. Ability to solve complex analysis and insights to effective business strategy
  • Prior experience in a role requiring collaboration across multiple functions within an organization
  • Proven ability to drive each project to completion with minimal guidance while effectively managing multiple projects at a time


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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Data Scientist (Analytic Consultant 5)

Wells Fargo
Minneapolis, MN

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Wells Fargo
Minneapolis, MN

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