Krishna Vardhan Diggavi

Quantitative Investment Intern at State of Wisconsin Investment Board
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Contact Information
us****@****om
(386) 825-5501
Location
Chicago, Illinois, United States, US
Languages
  • English Full professional proficiency
  • Hindi Full professional proficiency
  • Telugu Full professional proficiency
  • Kannada Native or bilingual proficiency

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Credentials

  • Programming for Everybody (Getting Started with Python)
    Coursera
    Dec, 2021
    - Nov, 2024
  • Python Data Structures
    Coursera
    Dec, 2021
    - Nov, 2024

Experience

  • State of Wisconsin Investment Board
    • United States
    • Investment Management
    • 100 - 200 Employee
    • Quantitative Investment Intern
      • Jun 2023 - Aug 2023

      ● Framework Architecture: Architected an automation framework to assess data quality in the Commingled Fund process, involving external managers and risk systems like Factset, using Snowflake SQL. ● Portfolio Construction: Analyzed the research on the utility of Factor Premia in the context of Total Portfolio Management, focusing on long-term risk and return characteristics of a portfolio. ● Optimization: Collaborated with PMs and IT to develop and optimize Snowflake-based Investment… Show more ● Framework Architecture: Architected an automation framework to assess data quality in the Commingled Fund process, involving external managers and risk systems like Factset, using Snowflake SQL. ● Portfolio Construction: Analyzed the research on the utility of Factor Premia in the context of Total Portfolio Management, focusing on long-term risk and return characteristics of a portfolio. ● Optimization: Collaborated with PMs and IT to develop and optimize Snowflake-based Investment Committee reports, instrumental for the CIO and asset class heads. Show less ● Framework Architecture: Architected an automation framework to assess data quality in the Commingled Fund process, involving external managers and risk systems like Factset, using Snowflake SQL. ● Portfolio Construction: Analyzed the research on the utility of Factor Premia in the context of Total Portfolio Management, focusing on long-term risk and return characteristics of a portfolio. ● Optimization: Collaborated with PMs and IT to develop and optimize Snowflake-based Investment… Show more ● Framework Architecture: Architected an automation framework to assess data quality in the Commingled Fund process, involving external managers and risk systems like Factset, using Snowflake SQL. ● Portfolio Construction: Analyzed the research on the utility of Factor Premia in the context of Total Portfolio Management, focusing on long-term risk and return characteristics of a portfolio. ● Optimization: Collaborated with PMs and IT to develop and optimize Snowflake-based Investment Committee reports, instrumental for the CIO and asset class heads. Show less

  • Neuberger Berman
    • United States
    • Financial Services
    • 700 & Above Employee
    • Quantitative Research - Project Lab
      • Jan 2023 - Mar 2023

      ● Predictive Modelling: Developed predictive models using Multinomial Logistic Regression to determine bond under/overvaluation, and back tested with a long-short trading strategy. ● Machine Learning: Leveraged K-means clustering with company fundamental analysis to identify bond mispricing. ● Predictive Modelling: Developed predictive models using Multinomial Logistic Regression to determine bond under/overvaluation, and back tested with a long-short trading strategy. ● Machine Learning: Leveraged K-means clustering with company fundamental analysis to identify bond mispricing.

  • EY
    • United Kingdom
    • IT Services and IT Consulting
    • 700 & Above Employee
    • Quantitative Research - University of Chicago, Project Lab
      • Oct 2022 - Dec 2022

      ● Execution Analysis: Analyzed company's ESG indicators and studied ESG contract trade execution and regulation. ● Derivative Pricing: Implemented pricing of Sustainability-Linked Derivatives (European & American Binary Options) on KPI using Binomial Tree, Black-Scholes, and Monte Carlo Simulation models. ● Execution Analysis: Analyzed company's ESG indicators and studied ESG contract trade execution and regulation. ● Derivative Pricing: Implemented pricing of Sustainability-Linked Derivatives (European & American Binary Options) on KPI using Binomial Tree, Black-Scholes, and Monte Carlo Simulation models.

  • UBS
    • Switzerland
    • Financial Services
    • 700 & Above Employee
    • Market Risk Analytics Specialist (Authorized Officer)
      • Feb 2022 - Aug 2022

      ● Market Commentary: Generated Executive Risk Summary reports, highlighting market risk commentary on Value-at-Risk (VaR), Stress movements, and Back-testing exceptions. ● Risk Management: Owned Combined Stress Testing (CST) and Loss Potential Analysis (LPA) processes for the Market Risk models reported to the FINMA and FED.

    • Quantitative Risk Analyst
      • Jul 2019 - Jan 2022

      ● FRTB: Analyzed the FRTB implementation in adherence to Basel III's market risk framework using SA and IMA models, documented and communicated results to stakeholders. ● RWA: Automated the Risk-Weighted Assets (RWA) forecasting and allocation process, essential for regulatory capital requirements, using Python, thereby significantly reducing turnaround time by 80%.

  • UBS
    • Switzerland
    • Financial Services
    • 700 & Above Employee
    • Quantitative Risk Analyst Intern
      • Jul 2018 - Dec 2018

      ● Data Engineering: Engineered real-time PowerBI dashboards and Alteryx workflows to handle risk sensitivity data, expediting review and sign-off procedures for market risk officers. ● Data Engineering: Engineered real-time PowerBI dashboards and Alteryx workflows to handle risk sensitivity data, expediting review and sign-off procedures for market risk officers.

  • Birla Institute of Technology and Science, Pilani
    • India
    • Higher Education
    • 700 & Above Employee
    • Placement Coordinator
      • Aug 2017 - Jul 2018

      •Leadership - Successfully hosted, handled, and managed the Recruitment Season for the Year 2018-19 with the Placement Statistics of 97.5% •Team Management - Led a team of 70+ students and managed the recruitment of 1000+ students •Leadership - Successfully hosted, handled, and managed the Recruitment Season for the Year 2018-19 with the Placement Statistics of 97.5% •Team Management - Led a team of 70+ students and managed the recruitment of 1000+ students

Education

  • University of Chicago
    Master of Science - MS, Financial Mathematics
    2022 - 2023
  • Birla Institute of Technology and Science, Pilani
    Minors, Finance
    2017 - 2019
  • Birla Institute of Technology and Science, Pilani
    Bachelor of Engineering, Civil Engineering
    2015 - 2019

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