Sep 2022 – Present · 3 yrs 7 mos · Bengaluru, Karnataka, India

• Developed an orchestrated Python algorithm based on risk–return profiling to screen 80K+ UK investment funds, identifying high-conviction opportunities for wealth managers; optimized $10B+ client portfolios and reduced analysis time by 60%.
• Built a clustering model using machine learning to group and identify high-performing funds across asset classes, improving fund selection accuracy and portfolio diversification strategies.
• Building an AI Agent for equity, fixed income, and multi-asset funds using Python, SQL, and machine learning, enabling autonomous fund analytics, performance attribution, and portfolio recommendations.
• Developed an end-to-end Quant Analytics Portal integrating advanced ML models for fund screening, portfolio optimization, and risk analytics, empowering data-driven investment decisions for wealth managers.
• Led automation of 200+ investment factsheets by building scalable ETL pipelines, improving operational efficiency and reporting accuracy for $5B+ AUM across fixed income and equity portfolios.
• Redesigned monthly performance dashboards for 1K+ global funds ($50B+ AUM) to track performance KPIs and benchmark metrics, accelerating research and due diligence by 40%.
• Developed an automated ESG compliance tool leveraging financial APIs and NLP-based data extraction, streamlining reviews for 500+ funds and improving compliance accuracy for $10B in assets by 95%.
• Revamped global monthly fund reviews for 50+ underperforming funds, applying quantitative analytics, clustering insights, and predictive modeling to enhance strategy and investment performance.
• Analyzed and monitored CIO-selected investment themes, identified based on sector trends and technological advancements, to evaluate fund exposure and strategic alignment with market shifts.