Ruby (Weilu) Sun Email & Phone Number

Los Angeles, CA, US

Los Angeles, California, United States

• Spearheaded the formulation of the research agenda, integrating early alerts for users with health concerns
• Designed and executed a data ETL pipeline for TikTok data processing, automating extraction and cleansing of 600,000+ unstructured data points, achieving a 98% increase in efficiency
• Identified 12.89% negative comments through sentiment analysis using NLTK and VADER models of natural language processing (NLP) in Python; achieved a 4x efficiency gain and reduced project time by 1/3 through parallel.
• Utilized the SpanEmo prediction model to predict nuanced emotions of targeted audience for further segmentation
• Developed a Tableau dashboard to facilitate data-driven insights, receiving 91,300 views on Reddit

Los Angeles, California, United States

• Devised and executed analytics-driven enhancement strategies with targeted A/B testing for our mobile app
• Leveraged Tableau to analyze 500+ game elements data from top Tower Defense games, driving key strategies
• Automated workflows by converting data from Excel to XML, reducing manual effort by 50%
• Developed and improved sophisticated economic models to simulate in-game economies, ensuring the balance between supply and demand, significantly boosting in-game economic balance and user retention
• Enhanced communication among cross-functional teams and translated strategic objectives into actionable engineering tasks, fostering a 60% increase in goal achievement velocity
• Led a 12-member team, met tight deadlines, presented updates to 5 cross-functional teams per week, onboarded new employees, and enhanced collaboration with the Product Manager, accelerating project deliverables by 15%

Canada

• Consolidated and analyzed financial statements data, resulting in actionable outcomes and enabling senior management to strategic decision making that improved operational efficiency and business value by 15%
• Optimized database operations through advanced SQL queries, bolstering data integrity and accessibility across teams; utilized CRM to enhance operational workflows, reducing process cycle times by over 5 hours/month

United States

• Developed and implemented complex financial models, specifically pricing 200+ options using the Black-Scholes model in Python, enhancing predictive accuracy and client investment strategies.
• Applied Monte Carlo simulation for convertible bond pricing, simulating multiple price paths for underlying shares to average and discount payoffs to present value, enhancing the accuracy of bond valuation.
• Back-tested trading strategies and investment models using historical data, validating their robustness and reliability.
• Delivered regular presentations to senior management, translating intricate quantitative findings into actionable insights for non-technical team collaboration and decision support.

Shanghai, China

• Evaluated 400+ PE firms based on competitive advantages and creditworthiness, identifying the top 10% high-quality clients; assisted in designing transaction structures and conducted operational statistical analyses
• Collaborated with intermediary service agencies, including banks and investors, to streamline project facilitation
• Managed the disclosure and collection of private funds information; oversaw operations of private equity institutions

Beijing, China

• Engineered and refined complex financial valuation models for 5 high-potential acquisition targets, leveraging advanced Excel to perform sensitivity analyses and scenario planning
• Conducted in-depth due diligence, evaluating financial statements, operational processes, and corporate actions
• Utilized SEC Reporting and Capital IQ to screen potential companies, applying relative valuation techniques to pinpoint M&A targets, identifying opportunities that contributed to a portfolio expansion of over $100.

Nanjing, Jiangsu, China

• Maintained and refined intricate asset quality reports to equip senior management with key insights for risk mitigation and strategic decisions
• Enhanced clarity on expected credit loss projections
• Provided strategic advisory on credit risk, utilizing scenario analysis in Excel and economic trend evaluations
• Back-tested credit loss models against economic downturn scenarios to validate model robustness
• Optimized threshold settings for the divergence between actual and projected credit loss
• Advised 200+ clients for asset distribution; Customized investment portfolios and wealth management strategies

Master Of Science In Financial Engineering (Stem), Financial Engineering, 3.92/4.00

USC MS Honor Relevant Courses: FBE 551: Quantitative Finance (Python), ISE 537: Machine Learning in Finance ISE 535: Data Mining EE 512.

Master Of Science - Ms, Financial Engineering, 3.92/4.0

Bachelor Of Economics, Mathematical Economics, 3.85/4.00

Relevant Courses: C (Programming) Statistics, Mathematical Models, Mathematical Analysis Probability Time Series Analysis Advanced Algebra.