Data Architect

Lancy Lan

https://www.linkedin.com/in/lancylan/ 323-***-**** ***********@*****.*** Start date: Dec 2023 Open to Relocation EDUCATION

University of Southern California Los Angeles, CA

Ø M.S in Analytics GPA:3.88/4.00 01/2022–12/2023

Ø Concentrations: Data Mining/Modeling/Visualization/Interpretation(Python/R), Database Application Development(SQL) Lehigh University Bethlehem, PA

Ø B.S in Accounting & Business Information System GPA: 3.62/4.00 09/2017–01/2021 Ø Concentrations: CPA candidate, Financial Management, Information System Analysis and Design, Business Data Management SKILLS

Ø Technical Skills: SQL, Oracle SQL, Python (Pandas, NumPy, Matplotlib, sklearn, statsmodels.formula.api), R (caret, ggplot2, glm, KNN), Java, IDEA, Snowflake(AWS), SAS, Tableau, PowerBI, AMPL, A/B Testing, Arena, ETL, ELT Ø Microsoft Skills: Excel (Pivot-table, VBA), Visio, Access(Database,VBA), Azure, Adobe XD, SharePoints, PowerApps, Outlook WORK EXPERIENCES

Wilson Sporting Goods-DeMarini Oregon, OR/Chicago, IL Data Architect Intern 05/2023 – Current

Ø Digital Transformation: Independently designed and executed the transition from scattered data sources to a centralized Access database, replacing manual Excel entries; implemented automated data processing and reporting, optimizing efficiency by 95%, reducing processing time for general search requests from 5 minutes to 10 seconds. Ø Workflow Enhancement: Identified and addressed workflow inefficiencies in existing workflows through data analysis; presented solutions in department meetings, highlighting data issues, and suggesting solutions for enhanced efficiency. Ø Data Preprocessing: Executed data preprocessing procedures before migrating data to centralized database. Tasks included data quality enhancements, data integration, data transformation, data warehouse, data governance, data documentation, etc. Ø VBA Reporting: Developed user-friendly reporting interfaces using VBA, effectively presenting data insights to cross-functional teams. Contributed to informed decision-making through data-driven presentations. Beacon Assets Bethlehem, PA

Market Analyst Intern 05/2019 – 03/2020

Ø Data Preparation: Cleaned the company’s raw dataset by removing irrelevant factors, filling in missing values, extracting needed information from text, target encoding on categorical data, and transforming data type in Python Ø Predictive Modeling & Pricing Strategy: Fitted MLR models(statsmodels) on competitor dataset using different combinations of fields, applied the model with best performance indicators on our company’s properties to do price prediction, resulting in an average 15% increase in contracts after pricing adjustments Ø Marketing Strategy: Designed and executed monthly promotion strategy, analyzing its performance through EVM and presenting project progress to the management group. Managed the company's social media account and generated contents, resulting in a 500+ increase in official account followers and 42 leases from the target group in the summer of 2019 Deloitte Remote

M&A Part-time Assistant 09/2019 – 11/2019

Ø Market Analysis: Evaluated China’s early childhood education market for PE, VC, and strategic investors, analyzed market cap, major players, business models, and competitive advantages of top 10 brands Ø SQL: Created and organized store distribution database using SQL, improving data processing efficiency by 30% by retrieving specific datasets from database applications and transforming it into datasets suitable for market and service development, market penetration, and diversification analyses

Ø Python: Processed data frame using pandas and NumPy in Python to calculate daily percent changes of cumulative confirmed coronavirus cases, and visualized the impact of Covid-19 on various industries through line plots and time series analysis in Tableau PROFESSIONAL PROJECTS

Data Analyst for Credit Card Application Fraud Detection [2023] Los Angeles, CA Ø Data Preprocessing: Dealt with large dataset with 1 million records, designed solution approach, completed data quality report, visualized distribution of each field, detected anomalies, and fixed missing values/duplicates/outliers/inconsistent datatypes Ø Data Modeling: created over 4,000 new variables based on combination and variation of original fields through feature engineering, deduplicated and obtained top 20 variables with highest FS through filters and wrappers method, selected model with optimal set of hyperparameters through cross validation process

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