Sucheta Sudhakar Naik

+1-862-***-**** adexgy@r.postjobfree.com linkedin.com/in/suchetanaik/ https://github.com/suchetanaik

Objective: Data Enthusiast with 3.5 years of experience for interpreting and analyzing data for driving business solutions. Excellent proficiency in Python, R, SQL, MS Excel. Expert in preparing detailed solutions, business operations and analytics tools for effective analysis of data.

EDUCATION:

MS Information Systems & Analytics Rutgers University, New Jersey GPA:3.63 Dec 2018

MS Information Technology University of Mumbai, India GPA: 3.50 July 2016

BS Information Technology University of Mumbai, India GPA: 3.00 Nov 2013

TECHNICAL SKILLS:

Languages: Python, SAS, R, SQL, Java, JavaScript, MATLAB, Visual Basic (VBA), C, C#.

Tools and Frameworks: Hortonworks, AWS, RStudio, Tableau, Hadoop, HDFS, Weka, SPSS, JSP, JSON, HTTP.

Databases & Servers: Microsoft SQL Server, SQLYog, Big Query, MySQL Workbench.

Project Methodologies: AGILE, SDLC, Waterfall, Scrum, Kanban, Lean, Prince2.

Operating Systems Windows, Mac OS, Linux, Android, iOS.

Web Technologies: HTML, CSS, ASP. NET, Node.js,

PROFESSIONAL EXPERIENCE:

Lead - Customer Support Specialist at ContactEngine Inc, McLean, VA. Sep 2019 - Present

Python, Looker, JIRA, My SQL Workbench, SQL Yog, Microsoft Office Suite.

Promoted within a six-month timeframe for exceeding goals and supporting company culture.

Proactively monitored and audited conversation’s to identify and track solution issues/improve conversations using MS Excel, SQL for enhanced Customer Experience. Collaborated with the Innovation team for tagging conversations with Artificial Intelligence Intents to further train the AI models and improve the Machine Learning Engine.

Performed Market Trial Testing by building conversations for launching new product updates. Analyzed payloads using MySQL Workbench, SQLYog and provided customers with the analysis on a daily basis. Created Resynchronization process which saved truck rolls.

Provided user support and handled all escalated issues for all clients within Salesforce to bring down the average response time to < 10 minutes for each ticket’s arrival.

Data Analyst Intern at Paradyme Management, Greenbelt, MD. Sep 2018 – Dec 2018

Python, Tableau, RStudio, SQL, Microsoft Office Suite.

Implemented mathematical modelling & predictive analysis using Python to provide customer solutions, deliver results.

Analyzed healthcare data to identify the potential drug usage along with their consumers using Python and visualized using Tableau which would result in a decline of 12% in drug consumption.

Performed Regression techniques, Hypothesis Testing, Statistical Inference, Risk and Sensitivity Analysis, Forecasting and Optimization using Python on a variety of data sets that are created in SQL.

Data Analytics – Python Intern at TakenMind, New York City, NY. June 2018 – July 2018

Python, C, Microsoft Office Suite.

Performed data analysis, exploration and visualization using Python and associated libraries (Pandas, NumPy)

on functional data to reduce costs by visualizing the organizational structure for growth and strategy planning.

Data Analyst at University of Mumbai, Mumbai, India. Aug 2016 – Mar 2017

MATLAB, Microsoft Office Suite.

Built a deep Neural Network integrated with MATLAB application to find the patterns in satellite images provided by NRSA (National Remote Sensing Agency) to reduce the deforestation rate and the factors leading to it.

Performed initial pre-processing of data, training a Recurrent Neural Network and feed forward Neural Network using mean, variance, standard deviation, skewness and kurtosis to provide an accuracy of 89%.

Implemented Cross-validation, Euclidean distance and Probabilistic learning and parameters tuning for better performance and validation using K-fold validation approach resulting in 96.33% accuracy.

Data Analyst at Haptik Inc, Mumbai, India. May 2015 - Nov 2015

AWS, Java, JavaScript, MySQL, Microsoft Office Suite.

Created a cohesive deck using Java, AI, JavaScript, AWS, MySQL for providing chat insights from inception to completion. Worked on a system that supported a 100,000+ customer base.

Created S3 buckets in the AWS environment to store files, sometimes which are required to serve static content for an android application. Also, Configured Elastic Load Balancers with EC2 Auto-scaling groups.

Implemented RabbitMQ for Message Queuing based on AMQP and configured failover using AWS Route 53 and CloudWatch.

Business Analyst at Rabro Infotech, Mumbai, MH, India. July 2013 - July 2014

Java, VBA,, Microsoft Office Suite.

Automated process using Excel Macros, Pivot tables that improved reliability, productivity and mitigated financial risks.

Collaborated with offshore teams in Brisbane (AU) and Sydney (AU) using AWS, Statistical Analytics, JIRA, GitHub to create dashboards, impactful reports and visualizations in Tableau for customer satisfaction surveys and merge business processes.

ACADEMIC PROJECTS:

Heart Disease Prediction Model using Machine Learning (ML).

Developed models for heart disease prediction using machine learning and deep learning in python.

Implemented KNN, Decision Trees, Logistic Regression, Gaussian Naive Bayes, Support Vector Machines and Random Forest. Used heart disease dataset and statlog data sets from UCI machine learning repository

The future of insurance industry in a world of Autonomous vehicles.

Conducted a Marketing Research study to analyze the changes necessary in the auto-insurance industry to survive and thrive in a world with autonomous cars on the road by using Liberty Mutual Insurance as a test case using Qualtrics for surveys and SPSS for Data Analysis.

Analysis of Cardiotocography (CTG) data in R.

Using Machine Learning algorithm, we classified the fetal conditions as normal, suspect or pathological.

By using Random Forest Classifier and two features 'Fetal Heart Date's and 'Uterus Contractions' the state of fetus was determined. The highest accuracy of 94%, was achieved by Random Forest Classifier.

Classification of Learning Imaging Self-Scanning System-3 Images using LVQ1/2.

Learning vector quantization artificial neural network was used for classifying LISS-III satellite image.

Confusion matrix and Cohen’s kappa coefficient was calculated. Accuracy of the image was calculated as 97.22% and kappa coefficient as 0.9663.

RESEARCH & PUBLICATION:

Indian Education Vs. Foreign Education

Researched, Co-authored and published an article in The International Journal of Social Sciences and Humanities Invention Volume1 Issue 8 2014 (IJSSHI- ISSN 2349-2031).

Link: https://valleyinternational.net/index.php/theijsshi/article/view/118/119

Feature based Improved Classification of Satellite Image using LVQ Classifier

Researched, Co-authored and published an article in 2018 5th International Conference on” Computing for Sustainable Global Development” IEEE Conference ID:4283

Link: http://bvicam.ac.in/news/INDIACom%202018%20Proceedings/Main/papers/2877.pdf

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