Data Analyst Professional Experience

Maggie Jieyi Ma

**** **** ***, *** *********, CA

415-***-**** ac5ebf@r.postjobfree.com

linkedin.com/in/jieyima

github.com/jieyima

TECHNICAL SKILLS

Data Mgmt. SQL (Google BigQuery, MySQL), Extract-Transform-Load (ETL), Hive, Hadoop, HDFS Analysis Python (PySpark, scikit-learn, numpy, pandas), R (tidyverse, dplyr, glmnet) Visualization Tableau, Python (matplotlib, seaborn, plotly); R (ggplot2, shiny) ML KNN, Decision Trees, Naïve Bayes, SVM, PCA, Natural Language Processing (NLP) Tools Google Analytics (certified in 2016); AWS (S3, EC2, EMR, Comprehend); A/B Testing EDUCATION

2017 –

2018

M.S. Business Analytics (STEM)

University of California Davis, San Francisco, CA

• Focused on Machine Learning (ML), Big Data, Data Management

- Specific topics including SQL, AWS Cloud Computing, NLP, Lasso, ARIMA, Data Visualization 2013 –

2017

B.S. Finance (Honors)

University of Nottingham, Ningbo, China & Nottingham, UK

• Honors: 2017 Outstanding Graduate (top 5%), 2016 Provost’s list (1.5%), 2015 Dean’s list (10%) Copenhagen Business School, Copenhagen, Denmark, International exchange program

• Honors: Recipient of full scholarship from Chinese Government for being in top 1% of students PROFESSIONAL EXPERIENCE

2017 –

Present

Practicum Junior Data Analyst Autodesk, San Francisco, CA Consultant for ten-month engagement with Autodesk through UC Davis practicum project. Focused on drawing business analytical insights to predict the probability of log failure through ML techniques

• Developed a Spark MapReduce parser in Jupyter Notebook to transform ~30K records of unstructured log files stored in AWS S3 into structured metrics in AWS EMR

• Used Python to clean and mine data, applied supervised machine learning to predict log failures

• Built Tableau dashboards and delivered business insights to stakeholders at all levels 2016 Business Intelligence Analyst Intern Molbase Technology Co., Ltd. Conducted market analysis for Molbase, a chemical B2B marketplace providing e-commerce solutions encompassing more than 45 million customer transactions

• Built a Multi-Channel Funnel and a A/B testing model in Google Analytics to help target high- value customer segmentation, which saved 18% of SEM costs

• Performed SQL and maintained ETL pipeline of 8,000 transactional records into MySQL

• Analyzed and reported website traffic KPIs and provided ad-hoc analytics using Google Analytics 2015 Data Analyst Intern Mars, Inc.

Framed financial analysis for this leading Fortune 500 candy, food, and pet product company

• Performed analysis on quarterly data using SQL, Excel pivot tables and VLOOKUP

• Collaborated with cross-functional colleague on developing metrics and reported to manager

• Complied a mini playbook for future internship reference SELECTED MASTER PROJECTS

2018 Cryptocurrency Investment Analysis and Modeling, San Francisco, CA Predicted stock price of seven mainstream virtual currencies using machine learning models to draw prediction recommendations

• Deployed plotly and matplotlib for exploratory data analysis to visualize patterns

• Built time-series regression model on ~9,000 records to forecast the price trend of cryptocurrency

• Implemented cross validation to compare top performing models and decide the best regressor 2017 UC Davis Bookstore Inventory Analytics, San Francisco, CA Assisted bookstore management team in determining the optimal inventory level and minimizing unnecessary overstock

• Cleaned data and implemented exploratory data analysis of ~10K messy observations

• Built regression model in R to predict inventory level for next academic year with 95% precision

• Presented to bookstore management team an inventory solution to reduce overstock by 23%

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