Resume

Master of Science in Applied Cognition & Neuroscience, GPA 3.94/4.0
Specialization: Data Science/Computational Modeling, May 2018

Bachelor of Technology in Electronics & Communication Engineering, GPA 3.80/4.0
Specialization: Robotics & AI Engineering, July 2012

Languages:
- Advanced: Python, R, SQL, HTML, CSS, JavaScript, D3.js, Matlab
- Intermediate: SAS, C, C++, VBA
Databases: Oracle 11g, SQLite3, MySQL, MongoDB
Software Management: JIRA, HP ALM, IBM ClearCase & ClearQuest, Microsoft Office
Data Analysis Tools: Advanced MS-Excel, SPSS, Tableau, Google Analytics
Version Control: Git, Github Platforms: Windows, Linux
Frameworks/Libraries: scikit-learn, pandas, numpy, tensorflow, keras, seaborn, scipy, matplotlib, bokeh, Agile, Waterfall Model
Certifications: Machine Learning, Customer Analytics, ETL frameworks, People Analytics, R Programming, Neural Networks.

Worked on a project sponsored by DARPA to develop a Data Science tool (Data Driven discovery of models) to automate model discovery process for quantitative analysis mainly using d3.js, R, Python.
Research, design & development of DARPA funded project TwoRavens, (http://2ra.vn), a system of interlocking statistical tools for data exploration, analysis and meta-analysis, under the supervision of Dr. Vito D’Orazio (Prof. at the University of Texas at Dallas).
Developed several preprocessing measures and optimized machine learning algorithms (Clustering, Regression, Time Series & Classification) in R.
Designed and developed a report for providing exploratory data analysis on the uploaded dataset.
Formulated state-of-the-art statistical model comparison results to the user for measuring generalizability, not goodness of fit for the proposed models.
Developed the front-end UI using JavaScript, D3.js, jQuery, JSON, Mithril.

Worked on a project funded by NSF for enhancing the student experience in Online Learning systems through educational data mining & learning analytics under the guidance of Dr. Richard Golden.
Responsible for designing useful surveys & formulating hypothesis.
Design & evaluate hypothesis, preprocess data and variable selection, handling exceptions & assumption, develop models using machine learning in Python & Tensorflow.
Identifying the aspects of the course that requires more help for each student and dynamically providing cross-course content and other sources to explain in detail.

Worked in cross-functional teams including strategic planning & analysis, new business development, testing, and status reporting.
Optimized data collection procedures and conducted data exploration, quantitative research and data mining to uncover financial crime patterns.
Created visually impactful dashboards in Tableau for data reporting. Extracted, interpreted and analyzed data to identify key metrics and transformed raw data into meaningful, actionable information for reporting.
Used SQL to extract and sort data from the transaction database to create control groups for statistical analysis and modeling of the tokenized and EMV transactions for ROI patterns after product deployment.
Collaborated with cross-functional teams (Visa, Mastercard) to compile and validate data; reinforce and maintain PCI compliance standards.
Recommended functional approaches to address business requirements through use case models, workflow diagrams, data models, architectural process diagram for projects - ApplePay, Tokenization, EMV, Clover.
Developed automation tool in TACL and C for Electronic Funds Transfer (EFT) that reduced the testing eﬀort by 50%.

Formulated and implemented Data visualization charts for forecasting and inventory management using SAS 9.0 and SQL.
Designed a device that reported readings of individual phase current and voltages of any circuit using micro-controllers and Java program.