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Data Scientist (Analytic Consultant 5)

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 DMI’s 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 Fargo’s 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 consultative and visible role, you will support Customer Genome program. This initiative is 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 to generate innovative ideas, define analytical needs, create hypothesis, conduct data discovery, evaluate data quality, design quantitative analyses and experiments, build statistical models and machine learning algorithms, and generate business insight.

Key Responsibilities Include:

  • Conduct exploratory data analysis, mine data (e.g., clustering), and prepare modeling datasets from multiple data sources.
  • Conduct in-depth analyses of multivariate data using parametric and non-parametric statistical techniques, cluster analysis, PCA, and time series analysis to explore and understand the underlining mechanisms behind observed patterns.
  • Build, validate, 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).
  • Present model results and analytic findings; provide actionable recommendations to business partners to support data-driven decision-making.
  • Respond to ad-hoc requests from business partners to conduct data analysis to identify/quantify opportunities or address specific business questions.
  • 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.
  • Work with complex databases, conduct in-depth research to identify data issues, propose solutions to improve data integrity; perform other database-related analyses and projects as requested.


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 Big Data experience
  • 3+ years of statistical modeling 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, Java, MapReduce)
  • Advanced degree in quantitative discipline (e.g., Statistics, Economics, Computer Science, Applied Mathematics)
  • Strong programming skills using advanced statistical tools like R, Python, SAS, and MATLAB with ability to manipulate data for analytical purposes, conduct statistical data analysis, and build predictive models
  • Advanced knowledge of statistical techniques (e.g., probability, multivariate data analysis, regression, PCA, time-series analysis)
  • Solid understanding of and experience with machine learning techniques, such as decision trees, random forests, neural networks, SVM, ensemble learning, etc
  • Strong acumen diagnosing and resolving data issues to ensure accuracy and completeness
  • Exceptional analytical, critical thinking, quantitative reasoning skills, and problem-solving skills. Ability to relate complex analysis and insights to effective business strategy
  • Prior experience in a role requiring collaboration across multiple functions within an organization, strong business acumen, and ability to think strategically
  • Proven ability to drive each project to completion with minimal guidance while effectively managing multiple projects at a 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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