Engineering Data Analyst

AMOL A. KULKARNI

***, ********* ***** +1-814-***-****

State College – 16801 *******@***.***

Objective

Data analyst with experience in data science, machine learning, statistics and strong analytical skills looking to obtain a full-time opportunity in the data science domain, where I can apply my knowledge as an engineer and thereby contribute to the growth of the company, as well as fulfil my own aspirations. Work Experience

Research Assistant Penn State – Smeal College of Business, USA Nov 2016 - present

Development of cases and exercises for an online professional master’s course in marketing analytics

Assist with creating lecture materials related to marketing analytics, assisting students with technical questions/issues, and general research support for various cases/projects related to marketing analytics Data Analyst Consultant DecisionPro, USA Dec 2016 – Jan 2017

Development and implementation of R – code for panel data analytics.

Developing an UI for the implementation of panel data analytics. CFD Analyst Tata Consultancy Services, India Sept 2013- June 2015

Executed projects involving fluid extraction, meshing, mesh correction, design suggestion and analysis in an automobile for the flow of fluids, and heat transfer in various engine components and also various engines in different vehicle platforms.

Led the proposal of a new procedure for skin extraction for oil-spill analysis, thereby reducing the time taken to perform the analysis by 70% and saved $60000 per annum for the project

Developed an application that automated the entry of oil – flow for each crank angle of the crankshaft which saved 60% of the time required to complete the analysis.

Mentored new hires for the team.

Technical Skills

Machine Learning: linear regression, logistic regression, gradient descent algorithm, neural networks, backpropagation, support vector machines, dimensionality reduction, anomaly detection, Genetic Algorithms, Ant-Colony Optimization, Stochastic Gradient Descent.

Statistical Methods: time series, regression models, hypothesis testing and confidence intervals, principal component analysis and dimensionality reduction, Random forests, CART models, Clustering algorithms, Design of Experiments.

Software and Programming Languages: R Programming, Python, Octave, Microsoft Excel, Minitab, Lindo, Java, C, Autodesk, Master-Cam, WINQSB, Star CCM+.

Selected Coursework: Supply Chain Engineering, Linear Programming, Multi – Criteria Optimization, Design of Experiments, Applied Statistics, and Regression Modeling & Analysis using R, Data Mining, Computational Foundation for Smart System Design and Analysis, and Manufacturing Systems. Education

Master of Science in Industrial Engineering, Aug 2015-May 2017 The Pennsylvania State University, University Park PA Bachelor of Engineering in Industrial & Production Engineering, Sept 2009–June 2013 Sri Jayachamarajendra College Of Engineering, Mysore, India Kaggle Competitions:

Predict 2016 Us Presidential Election Voting Outcome

Used feature engineering, k-means, support vector machines, Decision Trees to predict the outcome with an accuracy of 85%.

Secured place in Top 10%.

Predict Likelihood of Survival of People on Titanic

Utilized k-means clustering, random forest, and decision trees to predict the likelihood of survival of people on the Titanic, with an accuracy of 86%.

Secured place in Top 10%.

Academic Projects

Framingham Heart Study

Developed a model to predict the risk of Ten - year coronary Heart Disease, performed dimensionality reduction using Principal Component Analysis and compared the performance of Linear Discriminant Analysis, Regularized Discriminant Analysis, and Quadratic Discriminant Analysis.

Anomaly Based Network Intrusion Detection

Designed and built statistical, feature selection and extraction systems for network anomaly detection and, developed a Network Intrusion Detection System, to identify and predict network intrusions using neural networks and random forests as underlying algorithms with an accuracy of 99%.

Predicting US Supreme Court Decision

Developed a regression model in R to predict the decisions taken by the US Supreme Court which are helpful for Politicians, NGO’s and firms, for 68 cases since October 2002 and compared it with the predictions of the experts in the field. Results – Model Accuracy: 75%. Experts Accuracy: 58%.

Personalized Ranking of International Universities for Higher Studies Developed a program that utilizes Analytical Hierarchy Process (AHP) and Borda ranking methods in generating a personalized ranking of universities to help international students make an informed decision on the university to attend.

Twitter Sentiment Analysis

Cleaning up irregularities, removing unhelpful terms, stemming and classifying tweets in R to understand the public perception of Apple by utilizing the publicly available data on Twitter. Certifications

Introduction to Machine Learning - Stanford University on Coursera Covered key modules of Linear Regression, Logistic Regression, Gradient Descent algorithm, Neural Networks, Backpropogation, Support Vector Machines, Dimensionality Reduction, Anomaly Detection, and Multi-variate Gaussian Distribution.

The Analytics Edge - MITx on edX

Covered key modules of Linear Regression, Logistic Regression, Regression Trees, Data Visualization, Text Analytics, Clustering, Linear Optimization and Integer Optimization.

Advanced Course in Automobile Technology - NIE, Eicher, Mysore Covered key modules of Working and assembly process of IC Engines, Detailed Working principle of- Intake

& Exhaust system, Lubrication system, Cooling system, Fuel system, Secrets of fuel economy, Product up- gradation

Extracurricular Activities

Placement Coordinator: SJCE- IP 2013 batch: Successfully placed 95% of the students

Part of a team that conducted the ‘Jayciana Green Run 2012’ as a part of the college fest of SJCE called ‘Jayciana’. Used the proceeds of the events to provide food to an orphanage and a home for senior citizens

Part of the team that organized sapling plantation event to commemorate the 49th anniversary of SJCE

Organized an Industrial visit to Manufacturing Facility of Toyota Kirloskar Auto Parts, Bangalore

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