Nishant Sahoo

Software Developer

Business Technology Analyst at Deloitte USI, Bangalore, India

Working as a Business Technology Analyst developing RPA tools using Python, Selenium, JavaScript, and Java which has reduced 72 hours of manual work to 3 hours of automation script execution.

Business Technology Analyst Intern at Deloitte USI, Bangalore, India

Interned for 6 months under Core Business Operations - Systems Engineering. Developed CRM enabled web applications using Oracle Engagement Cloud.

Data Science Intern at IBM, Bangalore, India

Interned for 8 weeks under Cognitive Computing and Advanced Analytics department. Developed a ChatBot to automate HR operations for a firm in the retail industry, and a document classification model for a firm in the finance industry.

Software Engineering Intern at Nagarro, Gurgaon, India

Developed a cross-platform e-commerce application using MERN (MySQL, Express, React, NodeJs) stack and electron.

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Software Engineering Intern at Maruti Suzuki India Limited, Gurgaon, India

Summer training: Interned for 6-weeks under the IT department, where I learned about the company's network technologies, and project management. I developed a Home Portal for the Engineering Division as my final project.

RPA Challenge

Developed an RPA system to solve the RPA challenge in a record time of 165 ms. Official website

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IMDB Genre Trend Analysis

Performed genre trend analysis using Python to analyse the shift in genre preferences of people in the world of cinema world from 1898-2019 and observed insights using Tableau.

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Developed a model to predict stock market behaviour for NASDAQ 100 companies using Twitter Sentiment Analysis.

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Developed a cross platform e-commerce application using MERN stack (MySQL, Express, React, NodeJs) as my final project during my internship at Nagarro.

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Fur Elise - Beethoven (Midi track)

Developed a midi track for Fur Elise using ScribbleTune, a Node.js module that helps you construct musical ideas with JavaScript String and Array functions and export them as MIDI files.

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IMDB Scraper

Developed a web scraper which retrieves a list of top 50 movies as rated by IMDB from the year 1898 to 2019 using Python and BeautifulSoup4.

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Behavioral Finance - What’s UP? Microsoft, or Amazon?

In this article, I’ll talk about how Harshini and I tried to predict the stock market behavior by using Sentiment Analysis on Twitter tweets about NASDAQ 100 companies. We used TextBlob (a Python library) to perform sentiment analysis, sklearn to build the classifier model, and collected the twitter tweets data set from followthehashtag official website.

Which movie should I watch?

In this article, I will illustrate how to scrape a list of top 50 popular movies for each year from 1898–present as listed on IMDb, 2018.

Work at CurioCity

• Web Developer - Developed a website for the NGO using HTML, CSS (Bootstrap) and hosted the page using Github Pages.

• Instructor - Taught English language to primary school students.

• Completed over 120 hours of community service.