Bhavan Gill
About Bhavan Gill
Bhavan Gill is a Quantitative Data Analyst at Legal & General in London, UK, where he has worked since 2019. He specializes in stakeholder management and data quality, and has a background in mathematics and actuarial consulting.
Work at Legal & General
Bhavan Gill has been employed as a Quantitative Data Analyst at Legal & General since 2019. In this role, he has contributed to reducing delivery timelines by two weeks every month through effective stakeholder management, which has enhanced team productivity. He collaborates with developers to design and implement tools that facilitate the seamless onboarding of new assets while maintaining data quality. Additionally, he manages a £5 billion portfolio, overseeing tasks such as redemptions, short sale adjustments, and book-cost reconciliation. His responsibilities also include booking trades amounting to approximately £50 million per month for Life Time Mortgage products.
Previous Experience at KPMG UK
Before joining Legal & General, Bhavan Gill worked at KPMG UK as an Actuarial Consultant from 2015 to 2019. During his tenure, he developed automation tools using Alteryx, Excel, and Python. These tools significantly reduced task completion time from hours or days to mere seconds, showcasing his ability to enhance operational efficiency.
Experience at Expand Research
Bhavan Gill began his career at Expand Research, a company of The Boston Consulting Group, where he served as an Associate from 2014 to 2015. This role provided him with foundational experience in data analysis and consulting, contributing to his professional development in the field.
Education and Expertise
Bhavan Gill studied Mathematics at University College London, where he earned a Bachelor of Science (BSc Hons) degree from 2008 to 2013. Prior to that, he attended Stanmore Sixth Form College from 2006 to 2008 and Villiers High School from 2001 to 2006. His educational background has equipped him with strong analytical skills and a solid foundation in quantitative analysis.