Marketing Data

Jianjian Xie

MOBILE: 646-***-**** • E–MAIL: ******@********.***

PROFESSIONAL SKILL

Professional: PYTHON (Data mining, Machine Learning, Data Structure and Algorithm, Web scraping),

Tensorflow (Deep learning & Computer vision), SQL(PostgreSQL), R (hypothesis testing, Bayesian analysis),

Experienced: Spark (MLlib), SAS (Advanced SAS certification), NoSQL (MongoDB), Tableau

WORK EXPERIENCE

Xiamen International Bank July 2014 – July 2016

Risk Analyst, Full time, Risk Control Department

Approval of Loans

Cover 2000 plus loans; assist with the decision-making process of approval based on the data and financial analysis (Excel, SQL).

Due Diligence management

Deliver inquiry and researches on personal and corporates’ financial statement, Improve the examination and approval procedure of loan and successfully decrease the percentage of non-performing loans by 0.8%

Claire's Inc. June 2013 – Sepetember 2013

Marketing analyst, Intern, Marketing Department

Maintaining company database (MySQL) and CRM system, making monthly marketing report

Preparing monthly marketing material and write scripts for PR activities

Nomura Research Institute.Ltd. March 2013 – June 2013

Intern, Consultancy department

Responsible for collecting information and Preparing materials for 5 consulting projects and contributed in these project research and communication.

PROJECT EXPERIENCE

Kaggle Competition Bronze Medal Winner: Mercedes-Benz Greener Manufacturing

Top 6% (224th/3825) in the competition. Work with a data set representing different permutations of Mercedes-Benz car features to predict the time it takes to pass testing. Use XGBoost, Logistics regression, Random forest, Ensemble learning(Python).

Kaggle Competition: Two Sigma Connect: Rental Listing Inquiries

Top12% in the competition. - Developed a multi-level ensemble model to accurately predict customers’ inquiry levels for rental listings. Deal with large scale data provided and various type of data, use XGBoost, Bayesian encoding for high cardinality encoding, StackNet ensembling (Python, Tensorflow).

DataCastle Big Data Competition Great Prize Winner

Participated in machine learning competition like Kaggle and finally be Top 10% in the competition. Use loan data to predict whether moral quality is good by data preprocessing, feature engineering, using different machine learning methods such as XGBOOST(Python).

EDUCATION

Columbia University, New York September 2016 – Now

Master of Applied Analytics, GPA 4.0/4.0

Shanghai Maritime University, Shanghai September 2010 – July 2014

Bachelor of Arts in Business Administration

Leadership: Vice President of Student Union

• Lead the biggest student organization and more than 100 students, successfully organized a number of Gala and Awards ceremonies

HONORS

The Outstanding Cadre of Shanghai. The Three-Good Activist of Shanghai.

The Shanghai Municipal-level Excellent Summer Practice Project

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