Candidates About

 

Elaine Qin

SUMMARY:

·             Highly efficient data scientist with 6+ years of experience in Statistical Analysis, Machine Learning, Data mining with large data sets of structured and unstructured data in banking, travel services, and manufactory industries.

·             Experienced the full software life cycle in SDLC, Agile and Scrum methodologies.

·             Skilled in Advanced Regression Modeling, Correlation, Multivariate Analysis, Model Building, Business Intelligence tools and application of Statistical Concepts.

·             Proficient in Predictive Modeling, Data Mining Methods, Factor Analysis, ANOVA, Hypothetical testing, normal distribution and other advanced statistical and econometric techniques.

·             Developed predictive models using Decision Tree, Random Forest, Naïve Bayes, Logistic Regression, Cluster Analysis, and Neural Networks.

·             Experienced in Machine Learning and Statistical Analysis with Python Scikit-Learn.

·             Experienced in Python to manipulate data for data loading and extraction and worked with python libraries like Matplotlib, Numpy, Scipy and Pandas for data analysis.

·             Worked with complex applications such as R, SAS, Matlab and SPSS to develop neural network, cluster analysis.

·             Strong SQL programming skills, with experience in working with functions, packages and triggers.

·             Experienced in Visual Basic for Applications and VB programming languages to work with developing applications. 

·             Worked with RDBMS including MySQL, Oracle SQL.

·             Worked with NoSQL Database including Hbase, Cassandra, MongoDB.

·             Experienced in Big Data with Hadoop, HDFS, MapReduce, and Spark.

·             Experienced in Spark 1.6, Spark SQL and PySpark.

·             Proficient in Tableau and R-Shiny data visualization tools to analyze and obtain insights into large datasets, create visually powerful and actionable interactive reports and dashboards.

·             Automated recurring reports using SQL and Python and visualized them on BI platform like Tableau.

·             Worked in development environment like Git and VM.

·             Excellent communication skills. Successfully working in fast-paced multitasking environment both independently and in collaborative team, a self-motivated enthusiastic learner.

 

 

TECHNICAL SKILLS:

 

Programming Languages	Python 2.x/3.x, R 3.x, SQL, SAS 9.x, Visual Basic for Applications, VB.NET, SPSS, Minitab, JMP
Data Visualization	Python 3.x, R-Shiny, Tableau 9.2
Databases	MySQL 5.x, Oracle SQL, HBase 0.98, Cassandra, MongoDB 3.x
Machine Learning	Regression analysis, classification, K-Means Clustering, Bayesian Methods, Decision Trees, Random Forests, Support Vector Machines, neural networks, Logistic Regression, Data Mining Methods, Factor Analysis, Cluster Analysis, recommendation systems.
Statistical Methods	Regression Models, Confidence Intervals, Bayes Law, Principal Component Analysis (PCA), Cross-Validation, Analysis of variance, ANOVA, Z-test, T-test, Hypothetical testing, normal distribution
Hadoop Ecosystem	Hadoop 2.x, MapReduce, HBase, Spark 2.x, PySpark
Packages	Pandas, numpy, scipy, scikit-learn, matplotlib, ggplot, ggplot2, dplyr, plyr, gsub, Spark SQL
Collaboration	Git, VM

 

 

PROFESSIONAL EXPERIENCES:

 

Client: TripAdvisor, New York, NY                              Aug.16 – Till Date

Data Scientist

 

Description:

TripAdvisor, Inc. is an American travel website company providing reviews of travel-related content. It also includes interactive travel forums. TripAdvisor was an early adopter of user-generated content. The website services are free to users, who provide most of the content, and the website is supported by an advertising business model.

 

TripAdvisor wants to adjust their hotel recommendations, but we don’t have enough customer specific data to predict. This project aimed at providing data processing and analytic solutions including adding customer parameters, data transformation/cleaning, machine learning and data modeling to create a model that will be more likely to accurately predict which hotel cluster will lead to a successful booking.

 

Responsibilities:

·             Involved in Design, Development and Support phases of Software Development Life Cycle (SDLC).

·             Collected, exported, merged and massaged data from multiple sources and platforms, and SQL Server to meet the analytical requirements.

·             Worked with cross-functional teams (including data engineer team) to extract data and rapidly execute from MongoDB through MongDB connector for Hadoop.

·             Performed data cleaning and feature selection using MLlib package in PySpark.

·             Performed partitional clustering into 100 by k-means clustering where similar hotels for a search are grouped together.

·             Used PySpark to perform ANOVA test to analyze the differences among hotel clusters.

·             Implemented application of various machine learning algorithms and statistical modeling like Decision Tree, Naive Bayes, Logistic Regression and Linear Regression using PySpark to determine the accuracy rate of each model.

·             Determined the most accurately prediction model based on the accuracy rate.

·             Used text-mining process of reviews to determine customers’ concentrations.

·             Delivered analysis support to hotel recommendation and providing an online A/B test.

·             Designed Tableau bar graphs, scattered plots, and geographical maps to create detailed level summary reports and dashboards.

·             Developed hybrid model to improve the accuracy rate.

·             Delivered the results to operation team for better decisions and feedbacks.

 

Environment: PySpark, Tableau, MongoDB, Hadoop, SQL Server, SDLC, recommendation systems, Machine Learning Algorithms, text-mining process, A/B test.

 

Client: Bank of America, Wilmington, DE                           Dec.15 – July.16

Data Scientist

 

Description:

Bank of America, is a multinational banking and financial services corporation. It is ranked 2nd on the list of largest banks in the United States by assets. As of 2016, Bank of America was the 26th largest company in the United States by total revenue.

 

Bank of America offers their customers a product recommendation system. This project aimed at developing and designing statistical models to predict which products customers would like to buy in the next month based on what they used in the past. We want to make customers be satisfied with our service and determine what kinds of products they will get in the future.

 

Responsibilities:

·             Participated in all phases of research including data collection, data cleaning, data mining, developing models and visualizations.

·             Collaborated with data engineers and operation team to find out stakeholders and specific business needs.

·             Collected, merged, massaged data from internal system to fit the analytical requirements.

·             Redefined many attributes and relationships and cleansed unwanted tables/columns using SQL queries.

·             Utilized Spark SQL API in PySpark to extract and load data and perform SQL queries.

·             Performed data imputation using Scikit-learn package in Python.

·             Performed data processing using Python libraries like Numpy and Pandas.

·             Worked with data analysis using ggplot2 library in R to do data visualizations for better understanding of customers’ behaviors.

·             Visually plotted data using matplotlib in Python.

·             Implemented statistical modeling with XGBoost machine learning software package using R to determine the predicted probabilities of each model.

·             Delivered the results with operation team for better decisions.

 

Environment: Python, R, SQL, Spark, Machine Learning Software Package, recommendation systems.

 

Client: 3M, Shanghai, China                                      Nov.14 – Aug.15

Data Analyst

 

Description:

The 3M Company, formerly known as the Minnesota Mining and Manufacturing Company, is an American multinational conglomerate corporation. 3M has operations in more than 65 countries including 29 international companies with manufacturing operations and 35 companies with laboratories. 3M products are available for purchase through distributors and retailers, and online directly from the company.

 

Our team will be responsible for e-commerce including taking text-mining process to improve the quality of service the customer scoring for the e-store. And providing an online A/B test to improve the profits.

 

Responsibilities:

·             Extracted customer reviews from Excel and import into R to do data analysis.

·             Used text-mining process to implement customer reviews and determine what service that customers were more likely to be focused on.

·             Conducted text-mining process each month since we should update the database all the time to keep focusing on customer feedbacks.

·             Delivered analysis focusing on promoting sales and providing an online A/B test.

·             Application of machine learning algorithms and statistical modeling in t-test and compared the significant difference.

·             Presented findings and data to team to improve strategies and operations.

 

Environment: R, text-mining process, A/B test and machine learning algorithms.

 

Client: Wellls Fargo, Des Moines, IA                                Jan.14 – Oct.15

Data Analyst

 

Description:

Wells Fargo & Company is an American international banking and financial services holding company. It is the world's second-largest bank by market capitalization and the third largest bank in the U.S. by assets.

 

The team will be responsible for database management as well as involving in all technical aspects of the system, including but not limited to application monitoring, responding to questions, researching issues, representing the application on production calls, participating in projects.

 

Responsibilities:

·             Involved in migration of various objects like stored procedures, tables, and views from various data source to SQL Server.

·             Preparation of data and mapping of ER diagrams that send business a good understanding.

·             Conducted ER diagram and coordinating with business executives.

·             Involved in Data Modeling using ERwin (Logical and Physical Design of Databases).

·             Optimized data collection procedures and generated reports on a weekly, monthly, and quarterly basis.

·             Presented findings and data to team to improve strategies and operations.

 

Environment: SQL, SQL Server, ER diagrams, ERwin.

 

Client: Video Center Media, Iowa City, IA                          Mar.11 – Dec.12

Data Analyst

 

Description:

Video Center Media opened its door for business in 1994.

 

Our team will be responsible for A/B test process to enrich contents and enlarge lead generations.

 

Responsibilities:

·             Extracted customer information from database using R.

·             Delivered analysis focusing on selling customer information to other companies and providing an online A/B test based on sending emails.

·             Changed the strategy according to the results of the test from emails to phone calls.

·             Application of machine learning algorithms and statistical modeling in t-test and compared the significant difference.

·             Presented findings and data to team to improve strategies and operations.

 

Environment: R, A/B test and machine learning algorithms.

 

EDUCATION:

Masters of Science in Business Analytics

Bachelors of Business Analytics and Information Systems & Economics