MANTHIRAMOORTHY CHERANTHIAN

773-***-**** adjeoa@r.postjobfree.com Chicago, Illinois-60612 LinkedIn Github Profile SUMMARY:

Graduate Student, AWS certified with 3 years of experience in Business Intelligence, Analytics. Looking for Business Intelligence, Data Science roles starting Jan 2021. Independent self-learner, Excellent problem-solving skills using data driven insights and strong business skills.

CERTIFICATIONS:

• AWS Certified – Solutions Architect – Associate, Cloud Practitioner, Tableau - Data Scientist, FAIR - Fundamentals. EDUCATION:

University of Illinois at Chicago Dec - 2020

Master of Science in Management Information Systems, 3.69 Courses: Data Mining Analytics in Healthcare Analytics for Bigdata Statistics for Management Advanced Database Management Systems Machine Learning Deployment Operations Management Marketing Bachelor of Electrical and Electronics Engineering Mar - 2016

EXPERIENCE:

Protiviti - Chicago, IL

Statistical Modelling Project Intern:

• Analyzed risk data generated using Monte Carlo Simulations using visualization techniques like Loss exceedance curves and Histograms following FAIR risk quantification methodology.

• Developed a visualization tool using Dash Plotly and deployed it as a web application using Heroku.

• Developed a framework to quantify and assess the impact of technical debt in an organization. Tata Consultancy Services - India

Systems Engineer (Business Intelligence and Analytics):

• Maintained history of transactions of the bank in a data warehouse hosted in Sybase IQ using ETL tools like SAP BODS, making it available for reporting and further data analysis by analytics team. Source business data includes loans, deposits, credit cards etc.

• Delivered significant managerial level dashboards (Monthly Channels dashboards, KPI’s etc.) using SAP Business Objects and Tableau assisting top-level executives in decision-making.

• Developed IFRS compliant reports using SQL for BASEL committee submission and for risk assessment.

• Optimized existing dashboards and reports’ loading time significantly using SQL window functions.

• Led a team of three reporting developers in a need for migrating 50 MIS Reports from SAP BO 3.1

(Desktop Intelligence) to SAP BO 4.2 (Web Intelligence) in 3 months as part of 1200 MIS report migration.

• Applied ML techniques like Logistic regression and Gradient boosting to predict loan defaulters of a Dubai based bank (Commercial Bank of Dubai) resulting in 10% reduction in defaulters.

• Assisted AIG Insurance during Quarter/Month end process as a backend support programmer. Academic Projects:

• ML deployment using Docker: Developed and deployed a cancer tumor detection ML model into AWS EC2 using Django for web framework, Docker for containers and Docker hub for publishing container images.

• Chronic Kidney Disease Prediction: Handled highly imbalanced dataset using sampling methods like over sampling, under sampling and created a Logistic regression model with high sensitivity and F-1 score.

• Parkinson’s Disease Detection: Developed a highly stable model to detect Parkinson’s disease from audio signals, which involves significant variable selection using stepwise regression, Interaction effects.

• Misinformation Detection in YouTube: Detecting Misinformation in YouTube videos by using NLP techniques in video transcripts, sentiment analysis and animated figure detection in videos using Topic Modelling (LDA), comments sentiment analysis and Image recognition using OpenCV, respectively.

• Sentiment Analysis using Spark Streaming: Sentiment Analysis of tweets for Costco and Walmart during COVID-19 using Spark Streaming, TCP Socket with real time prediction of tweets with model

• Self-taught the basics of accounting and finance independently. Aug 20 - Dec 20

Nov 16 - Jul 19

Aug 19 - Dec 20

SKILLS:

Software: AWS, SAP Business Objects, Tableau, SAP BODS, R studio, ServiceNow, MS Excel, Apache Spark, Risk lens. Programming/ Web Frameworks: R, SQL, PL/SQL, SAS, Python, HTML, Django, JSP. Relational Databases: Sybase IQ, Microsoft SQL Server, Oracle. Machine Learning Techniques: Linear and Logistic regression, Gradient Boosting, SVM, Clustering K-Means, Random Forest. Domain: Data Analytics, Data Science, Data Warehousing, ETL, Data Visualization, Machine Learning.

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