Data Scientist (contractor) Resume Sunnyvale, CA - Hire IT People

TECHNICAL SKILLS:

PySpark/Spark, Scala, Hive, NoSQL,Hadoop
Python, Scikit - learn, Turi Machine Learning Tools
ETL, Oozie
XGBoost, Random Forest, Deep Learning, Neural Network, SVM, Logistic Regression, Clustering, PCA, NLP, Topic Modeling, Recommendation Systems, R, SAS
SQL/MySQL, Neo4j, Qubole, Jupyter
C, Java, Linux Scripting
Github, Vision Control
AWS, Amazon S3

PROFESSIONAL EXPERIENCE:

Data Scientist (contractor)

Confidential, Sunnyvale, CA

Responsibilities:

Responsible for building new and additional features in the core product. Building a Journey Engine based on NLP, Text Cleaning, Text Mining and Aggregations.
Predictive models using XGBoost, Deep Learning (CNN/Word2vec), Regularization & Ensemble Modeling for customer behavior predictions
Recommendation Engines / Frequent Pattern Mining for customer needs
Forecasting and Segmentation problems using Text Clustering DBSCAN
Graph mining and Page Rank analysis

Data Analyst (contractor)

Confidential, San Francisco, CA

Responsibilities:

Analyzing large-scale data using Sequential Pattern Mining, Text Clustering, Topic Modeling and Predictive Modeling etc. with Python & PySpark
Generate Pipeline using PySpark, SparkSQL and Hive
ETL Scheduling and Deployment data using Python, HIVE and Oozie
Using Google Analytics and SQL to analyze data
Implementing API using Python

Data Analyst

Confidential, Fremont, CA

Responsibilities:

Using HIVE/SQL to extract, transform and store data and generate business metrics ; Conducting Feature Engineering and Data Preprocessing
Analyzing complex data sets, predictive modeling, machine learning, and/or large-scale data mining using PySpark & Python
Using ML tools and statistical models such as Classification, Gradient Boosted Decision Tree, Random Forest,Ensemble Methods, Logistic Regression, Cluster analysis, PCA and Semi-supervised Learning methods to solve real data problems
Conducting Text Analysis, Recommender Systems and script programming to analyze interesting problems

Data Analyst

Confidential

Responsibilities:

Data manipulation and Data management with R programming, descriptive analysis
Using various statistical models such as classification Decision Tree, Bayesian Analysis, Naive Bayes Spam Filtering, Logistic Regression, Cluster analysis, PCA, Neural Network, SVM, EM methods and script programming to analyze user behavior
Involving in reporting statistical findings to work colleagues and senior managers

Marketing Analyst

Confidential

Responsibilities:

Using statistical programming with SAS MACRO, SAS programming; SPSS,MS Access to analyze data
Using experimental design analysis, repeated measure analysis and hypothesis testing to study product performance
Conducting statistical analysis and survey of marketing, descriptive analysis, categorical data analysis, power analysis, nonparametric analysis