 Liaised with clients across industries, gathered their business needs, reviewed existing business processes & identified pain points, analyzed clients’ data, proposed advantages & recommendations in a strategic report Mined, cleaned & transformed financial & operations data using Pandas & Matplotlib in Python, devised a research framework, performed exploratory data analysis & hypothesis testing to derive data-driven insights Composed a prospectus for 10+ clients for successful listing, garnered 90+% returning customers for industry

 Extracted & processed 20+ macroeconomic indicators from Wind using Python Pandas & NumPy, automated exploratory analysis with visualization in Excel using VBA & enabled financial analysis for the company, saved ~1 hour daily in data processing efforts Led a team of 3 to review & prioritize 100+ daily macroeconomic news to discover novel investment strategies Analyzed 2-year historical data on PE positions & PB ratio, determined trend & patterns to empower fund managers with investment decisions for 13 company products, boosted product profit margins to 80%

 Liaised with cross-functional stakeholders to identify process risks & remediation steps, implemented hierarchical risk controls to support risk management process & reduced risks by 15% Investigated risk levels for loan projects & graded risks for loan units using custom SQL queries, based on 30+ derived KPIs related to company’s financial statements, cash flows and industry development Computed yield rates for 50+ loan projects, determined their risks & produced weekly product reports in Tableau

 Collaborated with 12+ team members for implementation of insurance products, performed statistical analysis with ANOVA & linear regression models using Excel & R, predicted sales with MAPE <10%. Designed insurance product formulae & controlled its pass rate within 15% using iterative approach.