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Data Analyst

Location:
Chicago, Illinois, United States
Salary:
50
Posted:
November 03, 2018

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Resume:

NISHANT KUMAR

ac7li6@r.postjobfree.com 646-***-**** Chicago, IL github.com/Nishantkumark

EDUCATION

University of Illinois at Chicago

Master of Science in Business Analytics (Data Science), GPA: 3.6/4.0 Expected December 2018

Anna University

Bachelor of Engineering in Computer Science and Engineering, GPA: 3.6/4.0 August 2010 – May 2014

SKILLS

Programming: R, Python, SAS, SPSS, Java, C++, Unix shell scripting, HTML

Statistical Techniques: Regression, Neural networks, ARIMA, Hypothesis testing, PCA, AB testing

Machine Learning: Classification, Clustering, Segmentation, NLP Text Classification, RNN, Recommendation system

BI Tools and Big Data: Tableau, Looker, scikit, SQL Server, AWS EC2, Hadoop, Hive, Spark, DB2, NumPy, pandas

PROFESSIONAL EXPERIENCE

Data Science Intern – 4C Health Solutions (Healthcare Analytics),Chicago, IL August 2018 – Present

Predicting patterns of drug abuse using Machine Learning – R, Python, SQL

Developed network analysis model to detect commonly misused drugs such as Opioids

Identified potential fraudulent pharmacy claims based on frequency of communities of drugs

Cleaned large and messy datasets to explore data and used techniques like Logistic Regression, Decision Trees, Random Forest, Boosting to identify fraudulent claims that increased revenue by $8M dollars

Operations Analytics Intern – TTX Company, Chicago, IL March 2018 – August 2018

Material Planning and Projection (Inventory Management/Operations): (Tableau, R, SQL Server, SAS, Excel)

Extracted data from databases and assessed data quality to perform data cleaning and apply descriptive statistics

Created dashboards using Tableau to project materials needed based on current demand

Developed analytical models to drive actionable insights that reduced wait time by 80% and automated the process

Re-shopping Analysis (Supply Chain): (Data Visualization: Tableau, R, SQL, SAS, Excel, Logistic Regression)

Used SAS for data manipulation and Performed Exploratory Data Analysis to identify patterns in component failures

Performed Logistic Regression to predict railcar repairs while improving performance by 80%

Documented the project and generated reports to present recommendations to key stakeholders

Data Analyst Intern – Centura Technologies, Bangalore, India September 2015 – October 2016

E-Commerce Project: (R, Tableau, Excel, SQL, K-Means Clustering)

Worked with product team to analyze the A/B testing results to provide recommendations on the new

experiments data for the mobile application called “mystore"

Applied statistical models to measure results and identify causal impact and attribution

Performed customer segmentation to understand consumer behavior which improved conversion rates by 18%

Analyst- Database Administrator – HCL Technologies, Chennai, India August 2014 – July 2015

Banking Project: (SQL, IBM DB2, Excel)

Developed, managed and tested database backup and recovery plans

Troubleshot High Availability Disaster Recovery (HADR) connection issues between primary and standby databases

Installed and tested new versions for DB2 and applied fixpack on existing versions to enhance performance by 70%

PROJECTS

Text Analytics with chat-bot August 2018 – December 2018

Twitter Interactive chat bot using Twitter dataset – Python (numpy, RNN, LSTM – tensorflow)

Created and trained a chat-bot by employing sequence to sequence model (RNN) trained on twitter text data

Dataset of 700k tweets and replies were pre-processed: padding, vocabulary generation and index lookup tables

The chat-bot responds in a single line to each line of user input with substitution of unknown words and proper nouns

Big Data- Machine Learning January 2018 – May 2018

Chicago DIVVY Bike Share Data Exploration – Databricks (Python, Spark SQL, Spark MLlIb)

Conducted analysis of millions of records in SparkSQL to apply clustering to identify common daily trip patterns

Found patterns based on origin, destination coordinates, and network graphs based on Weather Forecast

Improved location of bike depots which can help coordinate bike depot operations



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