SUMMARY:

6 years of consolidated professional experience with around 4+ years of experience as Application Developer in designing and developing large scale software applications for a CMMI - LEVEL 5 firm complied with best in business standards of SDLC via Agile. Master’s candidate in computer science with another added 2 years of production code experience in data science/machine learning with Django as backend for mining and collecting several interesting/peculiar insights that are buried under millions of records of data.

TECHNICAL SKILLS

LANGUAGE STACK, CORE SKILLS: Python, C++, C, Linux, Algorithms & Data structures, MySQL, Oracle12c, PostgreSQL, Django, Django Rest Framework, React Js

Infrastructure STACK: Docker, GitLab, GitLab CI/CD, Aws S3

DATASCIENCE, MACHINE LEARNING STACK: PANDAS, NUMPY, Neural Networks, Deep Learning, Natural language Processing, Keras, Tensor Flow, Supervised, Unsupervised algorithms, Data visualization, Bokeh, Seaborn, matplotlib

PROFESSIONAL EXPERIENCE:

Python Consultant

Confidential

Technologies used: Python 3.7, React JS, React-Redux, Docker, PostgreSQL, Django, Django Rest Framework

Responsibilities:

• Developing Rest API’s and microservices according to Client Requirements by leveraging Django Rest Framework
• Implemented Distributed Caching with Redis to take down the application response time from 4.5 seconds to 1.75 seconds latency
• Coding the Front-end components by using React Js framework
• Implemented PDF generation tasks using celery
• Test Driven development (TDD) using Unit test, Nose Module in order to design the API’s
• Analyzing and deriving Insights in the data sets using Python Numpy, Pandas Module
• Visualizing the reports, developing charts through Bokeh, Seaborn Packages

Software Engineer

Confidential

Technologies used: Python 3.7 virtual Environment, Keras, TensorFlow, Django, Flask, Machine Learning Algorithms

Responsibilities:

• Implemented and trained Deep Neural Network for classification of Malware with 96% accuracy in detecting Malware, deployed the same through Amazon Sage Maker.
• Developed APIs, Microservices with Django and Flask in order to store and retrieve the Machine intelligence which is acquired by the Trained Neural Network Model.
• Wrote Automated Testing Scripts in python to test the APIs using Nose an extension for unit test module.
• Developed Python modules to store files into AWS S3 bucket and share them to user when request is made from the portal.
• Added support for Amazon AWS S3 and RDS to host static/media files and the database into Amazon Cloud.
• Automation of deployment and testing process through Chef and Jenkins
• Scaling up projects using python tools like Multithreading, Collections, Data Structures, File Handling, celery
• Worked in BDD environment and wrote integration tests.

Graduate Research Assistant

Confidential

Technologies used: Python 3.6, Bokeh, Seaborn, PyLdavis, Gensim, PostgreSQL, Machine learning algorithms, keras.

Responsibilities:

• Data/Text Mining on congressional records (daily wide speeches in US senate) data through NumPy, Pandas, Dictionariception and serializing the data models to further visualizing the data, generating insights/reports and submitting in weekly team meetings
• Dynamic Topic modelling on approximately 20 million records (Big Data) by applying Gensim’s Latent Dirichlet Allocation (LDA) Algorithm resulting bag of vectors, Tweaking Term frequency- inverse document frequency algorithm for customary requirements and producing meaningful topics such that determining which topic occurred at which time and evaluating the growth/shrinkage of the topic in upcoming time periods by using deep neural network in keras framework.
• Visualizing time series data of those with Seaborn, Bokeh packages resulting in successfully identifying/understanding the correlation between certain topics across a given timeline, also visualizing each topic through PyLdavis for a better probability of discovering words with knowledge behind those.

Software Engineer

Confidential

Technologies used: Python 3, Django, Flask, PostgreSQL

Responsibilities:

• Restructured Labelling module as a Restful web service for better labeling of pathological results which will help the lead pathologists to quickly examine the results and better decision-making using Django Rest Framework.
• Implemented the Tables & Statistics module Micro service to generate the experiment results in the form of reports for scientific investigators to analyze the experiment using Flask.
• Designed, developed the In-life module micro service, which is the primary entry for collection, managing, reporting in-life data of species by study director using Flask framework.
• Implemented PostgreSQL backend infrastructure for the API’s in less than three sprints (original estimate is 8 sprints)
• Wrote Automated test scripts through selenium python framework for unit testing for each module and did integration testing across all the modules/components
• Conducted self, peer code reviews and wrote technical documents for each module and deployed the same in a centralized server so that the new entrants will have better knowledge transfer.
• Developed post receive web hook to auto trigger Jenkins build pipeline
• Configured Jenkins server with RHEL Linux server to automate continuous build and deployment of source code from bitbucket cloud using SSH remote host and SCP repository host.
• Used JSON, CSV as data exchange formats and Kafka as the messaging layer for handling high volume throughput of messages