SHENGCHEN LIN, CPA

Permanent Resident Houston, TX 77030 (open to relocation) 217-***-**** addpyu@r.postjobfree.com

Motivated data analyst passionate about leveraging data and advanced analytical tools to uncover interesting insights and improve business decision making process.

CORE QUALIFICATIONS

Technical: Advanced Excel functions, SQL, Python (pandas, numpy, scipy), Machine Learning (scikit-learn)

Analytical: Hypothesis Testing, A/B Testing, Business Process Valuation, Financial Analysis

Visualization: Tableau, Python (matplotlib, seaborn), MS Visio, PowerPoint

PROFESSIONAL EXPERIENCE

Tokio Marine HCC ($4 billion subsidiary of Global 250 Insurance Company Tokio Marine) Houston, TX

Business Analyst –Financial Audit September 2014 – November 2019

Developed analytical frameworks and evaluation metrics for business operations.

Built account receivable dashboards for internal reporting and identified 55% of total receivables with high risk of uncollectibility. Presented the finding to subsidiary CFO and proposed modifying collection strategy.

Traced and timely identified policies with low probability of loss after catastrophe by analyzing historical claims dataset. Freed 5M cash in reserve and improved performance ratios by 60%.

Performed descriptive analysis to uncover the trends in cash disbursements. Identified potential misclassified and fraudulent items for further investigation.

Validated data accuracy by reconciling key balances across systems and researched key drivers for variance.

Closely worked with financial directors to improve operational efficiency while keeping risks controlled.

PROJECT EXPERIENCE

Food Delivery –Operation Efficiency Analysis April 2020

Managed 5K data covering customer, merchant, and delivery information in SQL database.

Evaluated root cause for data integrity and performed data cleaning using Python to limit potential impact.

Presented and compared geospatial distribution for origination and destinations in Tableau dashboard.

Recognized 72% of total orders are delivered by bicycles and bicycle is the most efficient transportation method during dinner peak hours.

Recommended pre-ordering popular items and grouping orders with similar delivery path to improve process efficiency and stimulate revenue growth.

Fintech - Customer Churn Analysis February 2020

Uncovered trends and patterns in customer acquisition, retention, and churn by analyzing 1.3M personal loan applications from 158K applicants within 18 months.

Defined key metrics and cutoff time threshold for the evaluation. Visualized monthly active user trends and recognized 56% of the customers churned within the first year.

Identified top 5 indicators for churn by conducting Random Forest feature importance analysis.

Summarized critical user demographics for first year churned customers.

Built a supervised machine learning model for customer churn prediction and achieved 83% accuracy.

Online Education - User Experience A/B Testing December 2019

Designed and carried out A/B testing to evaluate the potential impact for a feature change.

Reviewed user journey, identified metrics, and proposed hypothesis for testing.

Compared the testing results for control and testing group, quantified the impact using statistical analysis and provided recommendations for follow-up experiments.

EDUCATION

Baylor University 2014

Bachelor of Business Administration, Double Major in Finance and Accounting GPA: 3.5/4.0

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