Karthik Anil Kini

Data Analyst Data Scientist Data Engineer

ML Engineer Software Engineer

**** * ******* ***, #***

Chicago, IL

Phone: 312-***-****

Email: admphf@r.postjobfree.com admphf@r.postjobfree.com

LinkedIn: https://www.linkedin.com/in/karthik-kini/

GitHub: https://github.com/karthik-kini-3

Education:

MASTER’S IN COMPUTER SCIENCE AND MATHEMATICS, ILLINOIS INSTITUTE OF TECHNOLOGY, CHICAGO

AUGUST 2019 – MAY 2021

Cumulative GPA: 3.91/4.0

BACHELOR’S IN TECHNOLOGY, COMPUTER ENGINEERING, SARDAR VALLABHBHAI NATIONAL INSTITUTE OF TECHNOLOGY, SURAT

JULY 2015 – MAY 2019

Cumulative GPA: 8.3/10.0

Summary:

Data Science Enthusiast with a hands-on and professional experience of 2 years in Computer Science and Statistics. Actively seeking full-time Data Science opportunities.

Skills:

oProficient in Machine Learning, Computer Vision, Deep Learning, Statistics, Competitive Coding.

oPython (Proficient), R (Proficient), Microsoft Azure (Proficient), Amazon Web Services (Intermediate), Google Cloud Platform (Proficient), Hadoop (Intermediate), Apache Spark (Intermediate), Snowflake (Intermediate), SAP (Intermediate), Microsoft SQL Server (Proficient), C (Proficient), C++ (Proficient), Core Java (Proficient), Octave (Proficient), MySQL (Proficient), JavaScript (Intermediate), AngularJS (Intermediate), Firebase (Intermediate), Microsoft Office (Proficient), Git (Proficient), Tableau (Intermediate), PowerBI (Intermediate).

Projects/Publications:

Masters

oDatabase System [project]: Implemented the following components in C:

Storage Management: It is capable of reading blocks from a file on disk into memory and writing blocks from memory to a file on disk.

Buffer Management: It manages a buffer of blocks in memory including reading/flushing to disk and block replacement (flushing blocks to disk to make space for reading new blocks from disk)

Record Management: It allows for navigation through records and inserting and deleting records.

B+ Tree Index: The index should be backed up by a page file and pages of the index should be accessed through the buffer manager.

oDivvy Bike Analysis [project]: Worked on four hypotheses for the group project:

Predicted the need for bikes according to the season in Chicago to ensure that the customers do not have to wait for more bikes, by ensuring the increase or decrease in the number of bikes at the docking station to maintain the profit. Implemented various regression models in R.

Predicted which station needs more docks based on the traffic (to and fro) at the station keeping in mind the revenue generated v/s the cost required to build more docks. Implemented the KNN Classification, Logistic Regression, and Naive Bayes Classification algorithms.

Identified the need and feasibility (revenue) for new stations between 2 stations for providing parking spaces at heavy traffic stations ensuring that divvy does not lose customers, based on the parking docks unavailability. Implemented the KNN Classification, Logistic Regression, and Correlation applying multi regression models.

Identified the time/season so that the bikes can be put for maintenance so that the Divvy company does not lose any revenue by putting the bikes into maintenance. Implemented the Decision Tree Algorithm, the Random Forest Algorithm, and the Support Vector Machine algorithms.

oWater Height Predictor [project]: Predicted the height of oscillating water from a sprinkler in Python using TensorFlow and Keras. Implemented a linear model, Deep Neural Network (DNN), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), and deep RNN on a synthetic time series data.

oCustom DLIB shape predictor [project]: Prediction of facial landmarks (face shape and eyes) on video stream in Python using an ensemble of regression trees on iBug 300-W dataset. I have used the AWS DeepLens system to record the live stream and created Docker containers to host it in AWS SageMaker. Performed hyperparameter tuning to identify the best hyperparameters for the predictor model.

oGitHub Issue Tracking: Extracted Issues from a Github repository and predicted for all types of issues using TensorFlow, FBProphet, and Statsmodel (ARIMA) APIs.

Bachelors:

oDisaster Management and IoT [project and publication]:

Real-Time Collaborative Processing for Event Detection and Monitoring for Disaster Management in IoT Environment.

Implemented the system in Python, AngularJS, Firebase using Arduino, Raspberry PI (Model 3B), Gas Sensors (CO2 and NO2).

Published our approach and its architecture at 10th ICCCNT and IEEE.

oText Recognizer and Translator [project]: Implemented a web-based tool using Google Cloud Vision and Google Translate API in python flask (backend) and JavaScript (front end) to recognize texts and translate them into any language based on requirements.

oImage Compression tool [project]: Implemented a tool using discrete cosine transform implemented in MATLAB.

oGrade Prediction tool [project]: Implemented a tool to predict final grades in Python and JavaScript using Support Vector Machines.

Experiences:

APRIL 2021 – MAY 2021, Data Analyst (Visualization) at University of Chicago

oWorked with Biomedical Big Data in the form of clinical data, sequence data, and the results of analysis at the Center for Research Informatics.

oCreating a web app to visualize different statistical correlation results.

oHelped the researchers to identify the trends between clinical and experimental data from different databases on a single platform.

oTech Stack: ReactJS (frontend) and Python Flask API (backend).

oCharts: implemented using ApexCharts.JS, React-Table, and Cytoscape.JS

FEBRUARY 2021 – MARCH 2021, Data Analyst at DATEN Solutions

oBuilding end-to-end scalable data science solutions.

oImplementing solutions in Microsoft Azure, Amazon Web Services, Databricks, Datarobot, and Dataiku.

oWorking on the following projects: Sentiment Analysis (LDA), Customer Segmentation (RFM), and Sales Forecasting (ARIMA).

oCreating CI/CD Pipelines using Azure DevOps, Jenkins, and TravisCI.

oCreating Data Migration and Data Validation Scripts in Snowflake.

AUGUST 2020 – DECEMBER 2020, Data Analyst at Accenture

oWorked in pairs throughout the term.

oIdentified biomarkers responsible for Alzheimer’s Disease from PubMed articles using ad-hoc spaCy matcher & regular expressions approach, and topic modeling using LDA (Latent Dirichlet Allocation).

oGenerated dummy COVID-19 patient dataset simulating 2 states.

oWorked on an AI tool to extract key attributes from PDFs and Images using OCR and NLP in Python.

oAnalyzed R&D expenditures, collaborations investment, net income/earnings for top 10 pharma companies.

MAY 2020 – JULY 2020, Data Engineer Intern at DATEN Solutions

oImplemented data warehouses for clients using Snowflake, SAP BODS, and Microsoft BI Tools.

oPerformed ETL (Extract, Transform, and Load) operations to create data cubes and data models.

oHelped to create dashboards for data analysis to get in-depth insights.

MAY 2018 – JULY 2018, Software Developer Intern at UGAM Solutions PVT LTD.

oA machine learning and image processing group project which identifies and analyses different brands on eCommerce advertisements (images & videos) implemented in Python.

oImplemented Multiscale Template Matching and T-distributed Stochastic Neighbor Embedding (t-SNE) approaches in Python.

oEliminated the manual identification and analysis of data and saved working hours significantly.

Achievements and Extra-Curricular Activities:

oData Science Capstone by Harvard University from edX.

oSequence Models for Time Series and Natural Language Processing by Google Cloud on Coursera.

oMachine Learning by Stanford University from Coursera.

oGoogle Cloud Platform Big Data and Machine Learning Fundamentals by Google Cloud from Coursera.

oDeep Learning with Keras and TensorFlow in Python and R by Start-Tech Academy from Udemy.

oSoftware Engineering Virtual Experience by JPMorgan Chase & Co from The Forage.

oMachine Learning A-Z™: Hands-On Python & R In Data Science from Udemy

oExecutive Member, ACM NIT Surat for 2015-16.

oParticipated in coding events on HackerRank, HackerEarth, LeetCode, CodeChef, Codeforces.

oAttended DotSlash, BuildChicago Hackathon, and HackerRank Virtual Career Fair.

o3D puzzle (e.g., Rubik’s Cube) solving enthusiast.

oTechnical writer, TechNews Magazine @ IIT [2020].

oCPS Test Proctor, Spring 2021.

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