Data Analyst

ANKUSH AGREKAR

312-***-**** ********@****.***.***

linkedin.com/in/ankush-agrekar github.com/aagrekar SKILLS

Machine Learning Feature Engineering,

EDA, Classification Methods (RF, SVM,

XGBoost), Clustering, Linear

Regression, Social network analysis.

Programming Languages R, Python,

MATLAB, Shell Scripting, SQL, PySpark

Tools MapReduce, Hive, Spark, HBase,

MySQL, DB2, Cloudera, Weka, R-

Studio, Jupyter Notebooks, SQLite,

Atom, MS Office.

Soft skills Proficient communication

skills, Self-motivated, Adaptability,

Quick learner, Ability to work under

pressure

RECENT COURSEWORK

Applied Statistics, Statistical Learning,

Big Data Technologies, Monte Carlo

methods in Finance, Data Preparation

and Analysis, Online Social Networking

Analysis, Data Mining

ACHIEVEMENTS

Barclaycard Annual Values Award from

the CEO of Barclaycard for saving

Barclaycard of the reputation damage.

Barclaycard Values Award for

Excellence for devising a work around to

the merchant statement problem.

Barclaycard Star Award for automating

scripts saving manual intervention and

time by around ~1hr daily.

CERTIFICATES

Natural Language Processing

Deep Learning

Reinforcement Learning

EDUCATION

Illinois Institute of Technology Master of Data Science CGPA 3.90 2017 Vishwakarma Institute of Technology B.E. Electronics Engineering CGPA 8.55 2012

WORK EXPERIENCE

Uptake Technologies Inc. Sponsored Project

May 2017 – Sept 2017

Assessed applications of data science in the IoT security domain. Performed exploratory data analysis to find feature interactions, identify attacks on various sensors and equipment.

Built models to classify the events as attack or non-attack with over 97% accuracy. [ XGboost, clustering, timeseries, PCA]

Barclays Technology Centre India Senior Support Analyst Nov 2012 – Jul 2016

Assisted in maintaining tier 1 and tier 2 applications which processed payments of nearly 350M GBP on a daily basis and generated statements worth 900M GBP.

Spearheaded in-depth analysis of a statement generation batch which was generating the merchant statements incorrectly and devised a work around that saved Barclaycard the growing reputation damage.

Developed scripts to gather daily stats and data which reduced manual efforts by around 10%.

ACADEMIC PROJECTS

Walmart Sales Prediction: Implemented Time Series modelling on Walmart’s Dataset available on Kaggle.com to predict the future store wise sales with R. Analyzed the data correlation using ACF and PACF and fit ARIMA model using forecast package in R to predict future weekly sales for a user input store and department.

HR Analytics: Analyzed HR dataset on Kaggle.com using R, to understand the primary factors that makes an employee leave an organization. Trained models like Logistic Regression, Naïve Bayes, Random Forest, SVMs and Neural Network to predict the next probable employee to quit and compared the results. Presidential Candidates Social Network Analysis: Scrapped data from Twitter using TwitterAPI for the 2016 Presidential candidates and analyzed their social connections and constructed network graphs to analyze using python. Facebook Community Detection and Link Prediction: Used Bill Gates connections from Facebook to build a network graph and analyze the different communities linked through him. We then predicted future links using Jaccard score in python.

Recommender Systems: Used data from MovieLens project which contained movie ratings from users and movie genres and predicted ratings for movies in the test set based on cosine similarity using python.

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