Sheng Zhu

Sheng Zhu-1

Managing Consultant

 

  • > AI and machine learning architecture 
  • > Data science and machine learning
  • > Advanced data analytics and statistics
  • > Regulatory and compliance SME
  • > Technical project management 

Background

I joined DMW in 2020, after five years as a self-employed independent Data Consultant. During this time, I gained extensive experience working on various data-driven projects in the Financial Services industry, and I developed as an AI and Machine Learning Architect.

Prior to self-employment, I led a data analytics team for five years in the insurance and asset management division of PwC and worked as a Data SME in a section 166 skilled person review with KPMG on behalf of PRA.

Before starting work, I obtained a Master’s degree from the University of Cambridge.

Outside of work, I am a keen runner and swimmer.

Skillset 

I am from a technical background and like to envision a tangible technical solution when facing client challenges.

Data has been always been close to my heart and I have been keeping myself up-to-date with the latest developments in data technology and methodology.

I have a particular interest in using data science and AI solutions to transform vast data sets into actionable insights and AI-driven automations.

I take a structured TOGAF (The Open Group Architecture Framework) methodology approach in architecture design domain and apply Agile in solution development.

Career Highlights 

I was the one of the lead solutions architects to design and deliver a self-service BI and self-service AI platform in the largest European bank. My specific domain was AI and machine learning architecture. By adapting Azure and Power BI technology, the solution has transformed the way the bank uses data and has enabled the bank to embrace a new era of AI.

I also worked as an independent Data Consultant in a UK retail bank and successfully led various vulnerable customer detection and treatment projects based on data science and machine learning methodology. The projects covered a wide range of retail and consumer credit products and have significantly reduced the banks operational overhead and regulatory risk exposures.

View more people: