Top Bank : The Enterprise Functions Technology (EFT) group provides technology solutions and support for Risk, Audit, Finance, Marketing, Human Resources, Corporate Properties, and Stakeholder Relations business lines. In addition, EFT provides unique technology solutions and innovation for Wells Fargo Technology, Enterprise Shared Services, and Enterprise Data Management. This combined portfolio of applications and tools are continually engineered to meet the challenges of stability, security, scalability, and speed.Within EFT the Corporate Risk Technology (CRT) group helps internal LOBs 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.

Within CRT the Calculation Services group is seeking a Big Data Engineer (Software Engineer Specialty) to work on qualitative and quantitative risk models for multiple LOBs. The position will offer the opportunity to work on the latest open-stack technologies in Big Data / Python universe.
Responsibilities include:

• Standing up cutting-edge analytical capabilities, leveraging automation, cognitive and science-based techniques to manage data and models, and drive operational efficiency by offering continuous insights and improvements.
• Help in design and implementation of algorithms and tools for analytics and data scientist teams.
• Use a variety of languages, tools and frameworks to marry data and systems together.
• Collaborate with modelers, developers, DevOps and project managers on meeting project goals.


* Below skills are must for candidate to succeed in this role.

  • Working experience on Hadoop
  • Strong knowledge of pyspark
  • Experience of handling machine learning models

** Ideal candidate would be someone who has implemented Hadoop based data science platform for leading financial institutions. Candidate should be able to debug complex PySpark code and machine learning scripts for performance optimization.