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Engineer Data

Location:
Chicago, IL
Posted:
October 15, 2020

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Resume:

MANTHIRAMOORTHY CHERANTHIAN

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

Graduate Student, 2x AWS certified with 2.7 years of experience in Business Intelligence, Analytics. Looking for Data science, Business Intelligence roles starting Dec 2020. 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 Courses: Data Mining Analytics for Big data Analytics in Healthcare Statistics for Management Advanced Database Management Systems Enterprise Application and design Marketing Operations Management. Anna University, Chennai, India

Bachelor of Engineering Electrical and Electronics Mar - 2016

EXPERIENCE:

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, treasury etc.

• Delivered significant managerial level dashboards (Monthly summary dashboards, KPI and BPI etc.) using SAP Business Objects and Tableau along with universe maintenance using SAP_IDT assisting top-level executives in decision making.

• Led a team of three reporting developers in a need for migrating 50 MIS Reports from BO 3x (Desktop Intelligence) to BO 4x 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) and reduced them by 10%. Assistant Systems Engineer:

• Worked as a 24/7 backend support programmer for AIG Insurance, roles include developing new ETL jobs, PL/SQL procedures etc. Assisted business users extensively during Quarter close processes. Academic Projects:

• ML deployment using Docker: Developed and deployed a cancer tumor detection ML model into AWS EC2 using Django for frontend, Docker for containerization 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.

• Survival Analysis for Prostate Cancer: To analyze the survival probability for patients diagnosed with prostate cancer after 7 years using variable penalizing techniques like Ridge/Lasso and boosting models.

• Misinformation Detection in YouTube: Detecting Misinformation in YouTube videos by using NLP techniques in video transcripts, sentiment analysis in comments and animated figure detection in videos using Topic Modelling (LDA), comments sentiment analysis (syuzhet) 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. Jan 18 - Jul 19

Nov 16 - Dec 17

Aug 19 – Jan 20

SKILLS:

Software: AWS, SAP Business Objects, Tableau, SAP BODS, R studio, ServiceNow, MS Excel, Apache Spark. Programming/ Web Frameworks: R, SQL, PL/SQL, Java, 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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