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.
The Enterprise Analytics and Data Science team is responsible for developing and deploying machine learning and AI solutions for a number of domain areas such as fraud prevention, credit risk, experience personalization, anomaly detection and operational cost improvement. Small teams of data scientists and engineers partner with business Subject Matter Experts and technology in delivering these solutions. Success for these initiatives is dependent on the right problem framing, the identification of data sources, frequent interactions with the business through the solutioning process, engagement with governance partners, etc. in addition to the actual data science work of building and testing predictive models.
We are looking for data engineering leaders who can a team of data engineers in the development of data processing systems and interfaces, which support data science efforts, with a focus on enabling scalable, high performance, distributed computing environments. Researches new data processing technologies, building prototypes as needed, and participating in related leadership activities. Contributes to the implementation of machine learning and statistical algorithms, including making them more efficient and scalable. As a leader of the engineering team and in collaboration with the Data Science team, works closely with scientists and contributes to the data transformation, modeling, and deployment efforts. Additionally the position would provide technical advice and guidance to the performers (as needed), at different key milestones within the engagement.
The ideal candidate on this effort would be an experienced data analytic leader, ideally with prior experience in the full Model Lifecycle Management process leading complex data transformation efforts and deploying statistical and data science models in production. They would need to be strong at understanding business situations in working with the data and technologies required for a given project that can aid decision making. They would have excellent people management and partnering skills.
Specialized Knowledge & Skill Requirements
• Demonstrated experience providing customer-driven solutions, support or service.
• Knowledge and experience using a variety of data transformation languages to implement and operate data science infrastructure assets (e.g., Spark, Scala, Anaconda, R, Python, C, C++, Hadoop, Hive, HBase, Pig, MapReduce and other Hadoop eco-system components).
• Understanding of Data Warehousing, Business Intelligence and ETL Tools.
• Demonstrated experience developing and managing complex technical projects involving parallel or distributed computing, including Hadoop, the Apache Stack and related technologies.
• Demonstrated experience working with or on a Data Science team and understanding of data transformations needed in support of data science.
• Familiarity with a wide variety of data formats and processing methodologies.
• Familiarity with relational database design and SQL scripting.
• Strong willingness to adapt, pivot, and learn as needed to address emerging opportunities and challenges.
• Knowledge of Cloud computing infrastructure specifically in the Big Data Space (e.g. Azure ADLS, HD Insight, Databricks, AWS EC2, Elastic MapReduce) and awareness of considerations for building scalable, distributed systems.
Data Science Infrastructure Design, Development, and Operations
• Determines high level system integrations, primary dependent systems and infrastructure needed to implement the proposed business idea.
• Participates in the definition and planning of analytical projects to solve complex business problems in the areas of data processing and scalable analytical and computational platforms.
• Develop means for automating data- and analytics-related systems and processes, as appropriate, to support data science activities.
• Develop and execute strategies for deploying ML models, both vanilla as well as complex models such as deep learning, probabilistic graphical models, etc.
Management/Leadership for Department or Unit
• Creates an effective work environment by developing a common vision, setting clear objectives, expecting teamwork, recognizing outstanding performance, and maintaining open communications.
• Develops staff through coaching, providing performance feedback, providing effective performance assessments, and establishing performance & development plans.
• Manages team capacity to support Machine Learning/Data Science projects.
• Analyzes business and technology trends related to data architecture, data engineering, data management, and high performance computing to provide expertise to management and resources within the company.
• Function in a collaborative technical consultancy role to routinely contribute technical expertise in discussions with other technology units in the enterprise.
As a Team Member Manager , you are expected to achieve success by leading yourself, your team, and the business. Specifically you will:
• Lead your team with integrity and create an environment where your team members feel included, valued, and supported to do work that energizes them.
• Accomplish management responsibilities which include sourcing and hiring talented team members, providing ongoing coaching and feedback, recognizing and developing team members, identifying and managing risks, and completing daily management tasks.
- 8+ years of experience in one or a combination of the following: reporting, analytics, or modeling
- 4+ years of management experience
- 4+ years of experience with Big Data or Hadoop tools such as Spark, Hive, Kafka and Map
- 2 + years of architecture, engineering experience, or a combination of both, with distributed storage and processing technologies
- A Master's degree or higher
- 4+ years of ETL, data warehouse and data analytics delivery experience on internal or external cloud platforms
- Demonstrated experience providing customer-driven solutions, support or service
- Knowledge and experience using a variety of data transformation languages to implement and operate data science infrastructure assets (e.g., Spark, Scala, Anaconda, R, Python, C, C++, Hadoop, Hive, HBase, Pig, MapReduce and other Hadoop eco-system components).
- Demonstrated experience developing and managing complex technical projects involving parallel or distributed computing, including Hadoop, the Apache Stack and related technologies.
- Demonstrated experience working with or on a Data Science team and understanding of data transformations needed in support of data science
- Familiarity with relational database design and SQL scripting.
- Knowledge of Cloud computing infrastructure specifically in the Big Data Space (e.g. Azure ADLS, HD Insight, Databricks, AWS EC2, Elastic MapReduce) and awareness of considerations for building scalable, distributed systems
- 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.