VIPIN AMAR

Denver, CO · 720-***-**** adcktc@r.postjobfree.com ·

EDUCATION

University of Denver, Daniel Felix Ritchie School of Engineering and Computer Science Denver, CO Master of Science in Data Science AUGUST 2018 ~ DECEMBER 2020 GPA: 3.6

Relevant Courses: Machine Learning, Data Mining, Algorithms, Database Organisation and Management, Calculus, Probability and Statistics, Data Science Tools, Python programming, Parallel & Distributed Computing Visvesvaraya Technological University (VTU) Bangalore, IN Bachelor of Engineering in Electronics & Communication AUGUST 2010 ~ APRIL 2014 Courses: Data Structures and Algorithm, Database management System, Computer Networks, Operating Systems, Signal Processing, Network Theory

TECHNICAL SKILLS

Languages: Python, R, SQL, C, UNIX Shell Scripting Tools Used: Tableau, Hadoop, MS Excel, Apache Spark, MS Office, Mark Logic, Qlikview Databases: MySQL, Postgres, Oracle, MongoDB, CouchDB, Neo4j, Redis ML Libraries : Scikit-learn, TensorFlow, Keras, Pandas, Numpy, Scipy, Matplotlib, XGBoost, StatsModels, Seaborn Certifications: AWS Cloud Practitioner, Machine Learning, Tableau EXPERIENCE

HCL Technologies Bangalore, IN

Software Engineer, Big Data AUGUST 2017 ~ JUNE 2018

Extracted, interpreted and analyzed data to identify key metrics and wrangled raw data into actionable information.

Optimized Map-Reduce programs, by minimizing the mapper output using compression which lead to faster runtimes.

Minimized human errors by documenting known errors and horizontally deployed and cascaded to the entire team.

Experience with the full software development life cycle of a Data warehouse, including requirement gathering, data mapping, and data dictionary, design, implementation, and maintenance.

Narrowed down on the areas that needed improvement by classifying user responses using scikit learn using NLTK to perform a bag of words. Created visualisations using python to present the results to clients. HCL Technologies Bangalore, IN

Software Engineer, Regulatory Reporting MARCH 2015 ~ JUNE 2018

Slashed down the number of fraudulent activities by employing an artificial neural network for real-time predictive analytics. implemented using Keras architecture.

Developed reports using Tableau 2018 to make informed business decisions proactively boosting productivity and validated the reports using SQL.

Implemented K means clustering to detect hotspots of fraudulent activities which helped business improve security where the need was more.

Created optimized SQL queries to fetch data faster, scheduled BI jobs as per the design flow using the Control-M tool.

Collaborated with Data architects and onsite coordinators in the data modeling activities.

Resolved ETL production issues, performed its recovery steps, implemented bug fixes. In the process involved in SDLC.

PROJECTS

Implemented Multi class logistic regression using Tensor Flow library.

Performed Random Forest classification in Python and R on datasets along with parameter optimization and exploratory data analysis to predict the class of new data.

Performed web scraping on Wiki pages using Beautiful Soup and using priority queues found shortest path between two links.

Performed Time series analysis to predict stock market data using R.

Implemented Regression using Random Forest, Decision trees, Multiple linear optimizing variable weights by ridge and lasso techniques on the same dataset and compared various error metrics in python.

Implemented Principle Component Analysis on multi-dimensional data for visualization.

Employed Linear/ Quadratic Discriminant Analysis, Support Vector Machines, and Naïve Bayes for classification.

Performed Kernelization on linearly inseparable data for Classification.

Built models based on OLS, GLM and Dashboards using Python and Tableau.

Developed python scripts to find and eliminate articulation points on the Facebook network graph.

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