Data Engineering

AIYNGARAN CHOCKALINGAM

ENGINEERING AND DATA ANALYSIS

Buffalo, NY 14226 +1-716-***-**** *************@*****.*** linkedin.com/in/aiyngaran-chockalingam github.com/aiyngaran

EDUCATION

STATE UNIVERSITY OF NEW YORK AT BUFFALO 2020

Master of Science in Industrial Engineering GPA: 3.93/4.0 ANNA UNIVERSITY, Chennai, Tamil Nadu 2017

Bachelor of Engineering in Mechanical Engineering GPA: 3.4/4.0 SKILLS

Machine Learning, Advanced Analytics, Statistics and Probability, Data Visualization, Web scrapping, Data mining, Data processing, A/B Testing, PowerPoint, AWS, Problem-solving, Creative thinking, Interpersonal skills. SOFTWARES

Python, R, SQL, Tableau, Minitab, Advanced Excel, Matlab. CERTIFICATIONS

Google Analytics Individual Qualification 2019

EXPERIENCE

Quality prediction to reduce waste in the iron ore extraction process CURRENT

Conducting an analysis of the Iron ore purification process time series (ARIMA and VAR) in R studio that helps to reduce the impurities by 11% produced in the process.

Addressed the problem of iron ore wastage by saving approximately 140,000 tons per year. Research at SUNY Buffalo - Crime rate analysis and prediction [link] 2019

Led a team of four in predicting the crime rates of counties of NY by gathering data from different public data platforms.

Performed SQL queries to join the data. Connected the database to R studio and carried out data-wrangling and created dashboards in Tableau.

Leveraged models like SVM, Random Forest, GBM to train the data that captured a variance of 98.5% and documented the findings.

When deployed would curtail the crime rates by 15 - 20%. Data analysis and design Intern, (TTRC), Bangalore, India 2017

Analyzed the climate data and created Tableau dashboard reports of the climate data.

Designed an air conditioning system for a villa of 400 sq. m and 1200sq.m partnering with the on-site construction team.

Gathered and exercised the climate, building and internal load data to calculate theoretical heat loads using Excel.

Computed the building energy cost using Hourly Analysis Program to determine the optimized values of duct sizes.

Generated reports of the analysis and the pricing . PROJECTS

Salary prediction to avoid under/overpaying by employers [link] 2019

Analyzed various factors influencing the salary in a data set of 152Mb like degree, years of experience.

Created a python program from defining to deployment for salary prediction with automated pipelines in Python Jupyter Notebook and derived statistical inferences about the findings.

Implemented machine learning predictive models and achieved an MSE of 357 that would help employers not under or overpay the employees.

Interactive visual tool - analyzing the reviews of hangout spots [link] 2019

As a group of two developed an interactive tool by Combining the dynamic data retrieved from 3 different APIs.

Presented visually the list of top venues within a certain radius using Seaborn, Matplotlib and folium.

Categorized the spots based on the reviews and rating together for a user attending a particular event using NLP in python to help the users plan their trip in advance.

Improving warehouse efficiency - Six Sigma 2018

Applied DMAIC principles to study and improve the efficiency of the warehouse of quality-tested products and analyzed the root cause.

Conducted time study for every process, analyzed Cp, Cpk Process capabilities of collected data in MINITAB.

Implemented Kanban system, optimized layout and pallet arrangement to cut down retrieval time by 15%. COURSE WORK

Advanced Data Analytics & Predictive modeling Manufacturing Data Analytics Programming for Analytics Quality Assurance Supply Chain Analytics Design of Experiments Six Sigma Operations Research.

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