Tiantian Liu
*** ***** ******, *** ******, NJ ***02 412-***-**** ******@********.***
LinkedIn: https://www.linkedin.com/in/tiantian-liu-tl/ EDUCATION
Columbia University New York, NY
Master of Science in Enterprise Risk Management (STEM) September 2018 - December 2019
• GPA: 3.75/4.0
• Course Highlights: Quantitative Risk Management, ERM Modeling, Financial Risk Management University of Pittsburgh Pittsburgh, PA
Bachelor of Science in Mathematics, Minor in German Language (Magna Cum Laude) September 2015 - April 2018
• GPA: 3.7/4.0
• Honors: 2015-2017 Dean's List, Scholarships of 2018 Culver Award
• Course Highlights: Mathematical Probability, Linear Algebra, Combinatorics, Ordinary Differential Equations, Calculus
• Exchange program in National University of Singapore for one semester SKILLS
• Programming: Python (sklearn, pandas, NumPy, matplotlib, seaborn), SQL (MySql, MS SQL Server, PostgreSQL)
• Software/Technology: Tableau, Google Analytics, Microsoft Excel, Asana, Apache Spark, @Risk, Bloomberg Terminal
• Statistics: Time series analysis, Hypothesis testing, Bayesian analysis
• Languages: Mandarin, English, German
WORK Lions Assurance EXPERIENCE Financial New York, NY Data Analyst Intern April 2020 – Present
• Collected data for over 10,000 Companies in AI, FinTech, and BioTech industries from database (Crunchbase)
• Conducted data cleaning and data validation in Python; analyzed data and reached insights for investment decision-making
• Created dashboards in Tableau to visualize important metrics of OurCrowd Funds and 2 target companies in Drone industry
• Partnered with a client to optimize their social media strategy; resulted in 35% increase in LinkedIn posting views
• Predicted the probability of a company exit by building supervised machine learning models in Python; reached 83% accuracy Phalanx Analysis Group San Francisco, CA
Data Analyst Intern August 2019 - October 2019
• Cleaned the dataset of 5,000 Spice suppliers in China using Excel functions such as VLOOKUPS and handled outliers using IQR method; analyzed the organized data using Pivot Tables; generated price insights about suppliers
• Visualized the suppliers' data by creating charts and interactive dashboard using Tableau; identified the top 5 suppliers and 3 best price regions for the client
• Improved the clients' supply chain cost-management strategies in China; reduced cost of goods sold by 10%
• Built a web-scrapper using Selenium in Python to collect hotel data in top 40 major cities in the US
• Analyzed the collected hotel data and visualized the data using Tableau; discovered 5 trends in terms of fixed costs PROJECTS San Francisco Crime Analysis in Apache Spark March 2020
• Built an ETL pipeline to analyze 2.2 million records of reported incidents from SFPD and a time-series forecasting model
• Discovered the seasonal trends and the variation of the spatial distribution of incidents based on Spark SQL and Dataframe
• Forecasted the number of criminal incidents in San Francisco per day by training and fine-tuning an ARIMA model Supply Chain Demand Forecasting and Data Management March 2020
• Developed a forecasting model in Python for a pharmacy chain store to predict future demand of nutrition products
• Analyzed over 180,000 historical sales data including visualizing data and handling missing data
• Built random forest models for carry-over products and new products respectively; tuned the parameter via grid search
• Improved the model performance by reducing 18% of the mean squared error than the baseline model A/B Testing Design and Analysis in Alteryx February 2020
• Designed a matched-pair experiment to A/B test the price of a chain spa company to increase its gross margin
• Performed an ETL process in Alteryx using tools like Filters, Join, and Summarize; matched treatment and control groups by similar trending and seasonality; analyzed the A/B testing results by A/B Testing tool in Alteryx
• Chose the optimized price and improved the gross margin by 66% per store per week