Financial Analyst Machine Learning

YONGSHI RUAN

She/Her/Hers

781-***-**** *.********@*****.*** LinkedIn

EDUCATION

CORNELL UNIVERSITY Ithaca, NY

Master of Science in Business Analytics August 2024

UNIVERSITY OF MASSACHUSETTS Boston, MA

BSc Management August 2021

WORK EXPERIENCE

Exelon Corporation Newark, DE

Financial Analyst (Contractor) Feb 2025 - Current

Developed monthly forecasts in Hyperion for energy portfolios, leveraging time-series analysis to improve accuracy by 15% and reduce budget variances.

Implemented a dynamic Excel forecasting model for project budgeting using advanced formulas (INDEX-MATCH, OFFSET) and scenario analysis tools, improving forecast accuracy by 15%

Managed monthly accruals using Oracle, ensuring GAAP compliance by reconciling contract liabilities, O&M expenses, and revenue deferrals.

Designed Power BI dashboards to track accrual trends, forecast-to-actual variances, and working capital metrics, enabling proactive adjustments by leadership.

InnovaAI Tech LLC San Francisco, CA

Business Analyst June- 2024 - Aug 2024

Integrated diverse data sources, including CRM systems, billing databases, and customer feedback to create a comprehensive customer behavior and interaction dataset in SQL; Conducted EDA, feature engineering and selection techniques to uncover hidden patterns of key churn indictors.

Designed machine learning churn classification models with logistic regression and random forest to predict customers who are at high-risk of churn (accuracy of 85%) and identify important features.

Collaborated with marketing and customer service team to develop targeted retention strategies based on important features from model insights, including personal offers and proactive outreach program, resulting in a 20% increase in campaign ROI, translated to an estimated $2 million in preserved annual revenue.

State Street Quincy, MA

Operation Associate II Aug 2022 - Feb 2025

Developed machine learning models to predict cash flow patterns and optimize mutual fund transaction processing, maintain >95% end-of-day accuracy; Designed predictive algorithms to forecast daily trading requirements, resulting in improved investment estimates and reduced overdraft incidents.

Utilized statical analysis and data visualization techniques to create comprehensive financial reports for audit purposes, ensure timely payments while identifying potential discrepancies, collaborating closely with the accounting team.

Created an automated pipeline using Python, SQL, MCH to analyze daily cash activity reports, enhancing the efficiency of fund transfer procedures and minimizing client overdraft fees.

PROJECTS

Risk Assessment for Loan Application June- 2024-August 2024

Engineered robust ETL pipeline using SQL and Python to process and validate credit data from multiple databases.

Developed random forest for credit risk prediction, achieving 87% precision and generate 300,000 in cost savings through improved default prevention; Collaborated in creating dashboard for real-time monitoring, automated risk scoring system, processing 10,000+ applications monthly with a 40% faster risk assessment than manual review time.

SKILLS & INTERESTS

ERP/Accounting: Oracle EPM, Hyperion, SAP FI/CO

Forecasting & Analytics: Python (Pandas, NumPy, Scikit-learn), SQL, R, ARIMA/Prophet

Big Data Tools: Google Cloud Platform, AWS, Azure

Visualization: Power BI, Tableau, Oracle Analytics Cloud (OAC)

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