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Click here or scroll down to respond to this candidateCandidate's Name Phone: PHONE NUMBER AVAILABLE
Email: EMAIL AVAILABLE
Key Skills
Fluent R; Python; Tableau; SAS; Web Analytics; Spark; SQL, Teradata Django,
java;
Advanced ML models: XGBoost, SVM, Extra Trees ,RandomForest
AutoEncoder, LM, glmnet, multivariate-regression. Advanced deep learning
CNN, RNN, LSTM with Keras, Tensorflow, Pytorch .Time-series predictive
modelling Ensemble techniques, and Clustering. Knowledge of ML Azure, and hand
-on experience of NLP projects. Knowledge of distributed model with ML Azure, Spark
(pySpark). A strong statistical knowledge with A/B testing GitHUB version control.
Data warehousing design and Data modelling projects.
Knowledge with Docker
Experience
Teaching Assistant for Database Management and Analytics.
Mentor 3 consecutive years of Undergraduate Research funded by NSF.
Awards
3 times Fellowships.
1 Scholarship
Interests:
Online learning
Meetup
Personal Data
Linkedin url:
https://LINKEDIN LINK AVAILABLE
Address:
11160 Jollyville apt 1324 Austin Texas, 78759s.
OBJECTIVE KN Production South Carolina June 2017- Aug 2019
Passion for cutting edge Data Scientist - remote
technology to help drive Digital marketing is very important for many business , especially for small
informed business decisions. business that want to grow in US. My work involves several related projects as
Applied cohort analytic to study customer behavior to clustering model.
Results-oriented with R & D
experience in computer Optimize weight portfolios. (Python)
science field with a strong Modelling anomaly detection model. (R)
interest on marketing and Build prototypes and setup AB testing. (R)
financial analysis, Provide technical support for junior data scientists.
particularly with time series Analyze products and built recommendation system to optimize
models. Experience with personalized marketing (Python)
advanced machine learning Built customer retention model (Python)
algorithms and BI tool. Long Modeling project for customer churn prediction (R)
life learning on different Built sentiment analytic model (NLP) for product reviews. (Python)
domain knowledge and self- Built ML model to segmentation market share for optimizing revenues. (R)
motivate to work
independent or a team KN Production, Colorado
member. Data Analyst Jan 2017-May 2017
Optimize queries on SQL Server and maintain consistency among different
WORK EXPERIENCE data sources. (T-SQL)
Retrieve data and make visual report with Tableau.
TCS/Apple, Data scientist
Sep 2019 -present Built model to predict the likelihood of marketing engagement
Predicting Gift card (Python)
Apply A/B testing to determine the effective of each marketing campaign .
sale is main work at
Manipulate/ wrangling data to clean format in large scale. (Python,R)
Apple business,
7 year python experience, >4 year R programming, 3 year SQL server.
however, big
Building prototype for several projects and automated model selection
challenge is to
with Python ,
monitor actual
Research Assistant, University of Colorado, Colorado Springs 2013-
trending sales and
2017
detect outliers out of
ML model selection project using Meta-learning approach. (Python)
peak sales due to
Author detection project using ML model on unknown text. (Python)
holiday and seasonal
Improve performance ML with Ensemble technique . (PySpark)
trend. My job is to
build an anomaly
Director of Computer Center, University of Foreign Languages and
model to flag out of
Technologies Viet Nam Jan 2000
normal for further
Dec 2009
investigation.
Manage the operation of computer center which provides IT service and IT
Not all group training courses for different departments.
merchants achieve Organizing on-site training in demand
their seasonal sales Collaborate with professional instructors in training staffs.
that needs a solution
to predict whether a
EDUCATION
merchant need to
launch a promotion Doctor of Philosophy in Computer Science, GPS 3.97, University of Colorado
program. This is the at Colorado Springs, 2017 . GPA: 3.97
goal for my second
Master of Computer Science, GPA: 3.5, Kansas State University, 2012
predictive modelling
with Apple.
Selecting promotion
strategy is a hard
problem for many
merchant to optimize
profit. I am study on
optimizing problem
that can be solved by
machine learning.
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