5 years of industry experience in Data Science/ Analytics, Master’s in Economics with Data Science Certificate
Overview
8
8
years of professional experience
Work History
Senior Data Science Analyst
Universal McCann
New York
07.2023 - Current
Media Analytics: Manipulate multiple sources of data to analyze the state our clients’ businesses across multiple dimensions (search interest, website visits, social media, advertising activity, TV presence)
Project Managements: Manage projects timelines and deliveries, while working and owning certain pieces of the projects independently, and present finding to key stakeholders
DataEngineering Quality Assurance: Maintain and lead conversations around Data Extraction Transformation Loading (ETL), Quality and Hygiene with Database Engineering teams
Data Scientist II Product Analytics
BOLD
San Francisco
06.2022 - 02.2023
Product Analytics: Collaborate with business partners to manage KPIs, conduct root cause analysis, write complex SQL queries to extract data, and communicate insights for executive reporting
A/B Testing: Design, analyze, and review AB tests and multivariate experiments to validate hypotheses, create reports and dashboards, provide insights to assist product pricing and feature launch decisions
Machine Learning: Use ML and statistical analysis to predict customer behavior and better understand the drivers of user engagement, retention, and funnel conversion
Data Scientist
Saks Fifth Avenue
New York
08.2021 - 03.2022
Marketing Analytics: Evaluated 5 sales promotion events with SQL, calculate incremental profitability and ROI, automate analytics ETL pipelines and KPI reports, to streamline campaign performance monitoring
Customer Analytics: Summarized profitability measurement of targeted customers with established metrics, identify 100+ suspicious consumer behavior patterns with statistical analysis to drive peak season planning
MachineLearning: Forecast conversion behavior of 3M+ target audience from their past purchase metrics, online behavior, demographic, and customer segments, using classification and propensity models
PredictiveModeling: Enhanced marketing resource allocation by uplift models, to quantify incremental response as of marketing communications, predict treatment effects with machine learning models
Data Scientist
Soothsayer Analytics
Detroit
09.2019 - 08.2021
MachineLearning: Analyzed customer segments and LTV using clustering, feature engineering, dimension reduction, and classification, to understand purchasing patterns and facilitate effective marketing
DataVisualization: Developed 15 interactive dashboards using Tableau, ETL pipelines, report automation as scalable BI solutions, and reduced process time with efficient SQL queries
DataEngineering: Set up ETL pipeline (Python, SQL) to standardize, and store millions of records data into a database, to enable faster exploratory data analysis (EDA)
MLExplainable: Interpreted machine learning models (e.g XGBoost) by applying SHAP and LIME to maximize production rate, prioritize resources, and minimize cost
Data Scientist Intern
Nova Technology
Ann Arbor
05.2018 - 04.2019
SQLDevelopment: Designed database by formal criteria to reduce data redundancy and improve data integrity
RecommenderSystem: Built recommender systems by collaborative filtering and evaluated by experiments