Silin Chen Email & Phone Number

New York, Ny, Us

New York, United States

• Lead Coverage Assessment Automation project as a project manager and coordinate business team and development team to ensure developments meet business requirements• Manage Screening System to update watchlist and mitigate risk associated with the identified issues• Manage AML Case Management system and work with technical/business teams to deploy new business requirements and conduct user acceptance test• Utilize Qlik Sense to build dashboards for transactions and alerts reporting and monitoring; update HTML to display dashboards and related reports and documents• Utilize SQL to perform analysis on transactions and alerts to find abnormalities and investigate• Conduct scenario threshold analysis for scenario optimization and threshold tunning; work in conjunction with business teams to perform user acceptance test and remediate issues with technical teams before implementation

Calabasas, California, United States

• Conduct research on Fannie Mae & Freddie Mac’s mortgage reports; utilize sophisticated Excel skills such as VLOOKUP and pivot tables to manage bivariable analysis and visualization• Utilize SQL skills such as join table to merge 450k+ entries of data and calculate D90 rate which is one indicator of borrowers’ default risk• Create 15 graphs by Python to visualize evolution of the D90 rate over time from loan age one month to loan age 36 months; show results in the dashboard• Select variables with low multicollinearity and build logistic regression model to predict default risk• Train and test the best logistic regression model with different datasets to get 15% more accuracy.

New York, New York, United States

• Conducted assessments of transaction monitoring alerts to ensure they adhere to all applicable policies, procedures, and regulatory compliance requirements.• Compared customer’s alerted transaction with transaction history and personal wealth• Documented alert analysis and clarifications related to the causes of warnings in order to determine whether the customer is engaging in money laundering• Created narratives and identified critical aspects that influence whether or not to pursue further investigation• Collaborated closely with Anti-Money Laundering investigation department to report decisions on referral or non-referral; processed and resolved 200+ client queries to ensure timely and satisfactory delivery of analytical results

Newburyport, Massachusetts, United States

• Applied Pandas to perform extensive data cleaning on sparse data; encoded categorical variables and standardized all variables; created a target variable from existing variables to measure farmer credit risk• Applied Statsmodels and Scikit-Learn to build supervised models including logistic regression, decision tree, and KNN and selected the best suited with highest test score and lowest MAE, MSE to predict farmer credit risk• Converted model performances into versatile visualizations to support actionable business decisions; conveyed to non-technical stakeholders with the most accurate modelodels to use.

New York, United States

• Spearheaded comprehensive research efforts into the rental market in the US’s 20 largest metro areas; compiled data and analyzed the most likely factors influencing Alpaca’s growth decision• Built a K-means model to determine the top 3 metro areas by taking New York and Boston as benchmarks; presented analyses on the expansion strategy to senior leadership

Shanghai City, China

• Analyzed Face Recognition technology market in China.• Evaluated market share, competitor performance, and methods to maximize sales volume.• Predicted future performance and presented findings and plans for developments to management.• Evaluated the effectiveness of marketing actions, recommended data-driven segmentation approaches, and delivered actionable insights to improve customer engagement and lifetime value.• Built and managed dashboards and reporting packages that inform day-to-day operations.

Nanjing, Jiangsu, China

• Reviewed, processed, and organized client information.• Made inquiries of clients’ credit record on Credit Reference Center.• Generated in-depth analysis of clients’ credit risk by applying the existing logistic regression model on SAS and reported findings to management.• Fostered relationships with potential clients and marketed various financial products.

Master'S Degree, Finance

Bachelor'S Degree, Accounting, Management