Experience

Mopid

• India
• Staffing and Recruiting
• 1 - 100 Employee

• Co-Founder & CTO

  • Jul 2023 - Present

  Bengaluru, Karnataka, India



ByteLearn.com

• E-learning
• 1 - 100 Employee

• Engineering Manager

  • Aug 2021 - May 2023

  Noida, Uttar Pradesh, India - Leading a team of 30+ FTE, including team of Frontend, Backend, DevOps, QA. - Built the team from scratch and product from the initial stage - Managing dependency across Product, design, developer and QA - Architecting solution for implementation and developing HLD's and LLD's for development - Database design and implementation - Managing the scalability and traceability aspect of the product



Sigmoidstar

• Education Administration Programs
• 1 - 100 Employee

• Co-Founder and Team Lead (Acquihired)

  • Sep 2019 - Jul 2021

  Gurugram, Haryana, India - Developed an education platform sigmoidstar.com for AI enthusiast and Data science people from scratch. - Developed video conferencing tool with AI features such as eye gaze, object detection for students to monitor there learning and give them feedback based on the same - Managed the scalability aspect of the product.



Yatra Online Ltd.

• India
• Travel Arrangements
• 700 & Above Employee

• Machine Learning Engineer

  • Dec 2017 - Sep 2019

  New Delhi Area, India Technology worked on : Flask, Spacy, CNN, Rtree, Nltk, Monetdb, Google Dialogflow, Google Adwords, AWS, Nosetest, Socketio, Jenkins, Gunicorn, Selenium. Chatbot: - Complete backend including nlp for chatbot. - Used Spacy and Google Dialogflow for rule based matching. - CNN classification for identifying the intent of a query for a user. - Standford Core nlp for breaking a query into dependent and independent clause. - Socket.io for handling switching between user… Show more Technology worked on : Flask, Spacy, CNN, Rtree, Nltk, Monetdb, Google Dialogflow, Google Adwords, AWS, Nosetest, Socketio, Jenkins, Gunicorn, Selenium. Chatbot: - Complete backend including nlp for chatbot. - Used Spacy and Google Dialogflow for rule based matching. - CNN classification for identifying the intent of a query for a user. - Standford Core nlp for breaking a query into dependent and independent clause. - Socket.io for handling switching between user and agent. - NLTK for sentiment analysis for identifying hotel with good amenities using trip advisor reviews. - Inhouse nearby api for nearby places using R tree. - Automation testing for the same. - Server setup for handling production setup. - Inhouse session managment for Google assistant. - Gunicorn for managing threads and workers. - Jenkins for server deployment. - Written nosetest for unit testing. - Integrated chatbot for Faq,desktop,ios,android,hotelar,Google Assistant,Google Home. Dynamic Discounting : - Api for instantly uploading discounting values directly to production and returning multi criteria discounting values. Also built a complete webapp for business for uploading discounting sheet directly to production. - Server set up for handling production hit for hotel B2C, flight B2C,flight B2B. - Server cluster set up. - Scraping for competitor discount values. - Handled 10k hits per min on produciton. - Gunicorn for managing threads and workers - Jenkins for server deployment - Written nosetest for unit testing. Sem adwords: - Automating the whole process of setting bids on a particular campaign based on gender,area,time of day Also had major contribution in some other projects, including IVR, Hotel Scraping, External FAQ Widget, Email Bot (for handling B2E clients’ travel request) and Internal FAQ Widget (for call center agents). Show less



ParallelDots

• United States
• IT Services and IT Consulting
• 100 - 200 Employee

• Software Developer

  • Jul 2017 - Dec 2017

  Gurgaon, India Working in the healthcare division of Paralleldots. ● Created webapps for tagging CT scans, And Bitewings image. ● Made aws server hipaa compliant and developed various code for dealing with PHI. ● Extracted data from hospitals pacs server. Technology worked on: Python, Flask, Aws, Git, Mysql, Nginx, Orthanc.



Sagacito Technologies

• India
• IT Services and IT Consulting
• 1 - 100 Employee

• Data Science Intern

  • Mar 2017 - Apr 2017

  New Delhi Area, India Worked in the ETL section generating various feature based on the raw data provided using Python, TalenD and Spark. ● Automated the testing of the feature generated using Python. ● Completed the ingestion flow for the data provided by the client by validating its schema and loading the required data to amazon s3 and mongodb in the required format using Java and TalenD and deployed airflow for scheduling the ingestion flow. ● Wrote various configurable code and general utility… Show more Worked in the ETL section generating various feature based on the raw data provided using Python, TalenD and Spark. ● Automated the testing of the feature generated using Python. ● Completed the ingestion flow for the data provided by the client by validating its schema and loading the required data to amazon s3 and mongodb in the required format using Java and TalenD and deployed airflow for scheduling the ingestion flow. ● Wrote various configurable code and general utility function for filtering raw data, mongodb insertion, schema validation, String approximation, date time handling, file handling from aws etc. Technology worked on: Python, Spark, Java , Hadoop, TalendD, Mongodb, Airflow, Aws, Git. Show less



grofers

• India
• Technology, Information and Internet
• 700 & Above Employee

• Data Analytics Intern

  • Jun 2016 - Aug 2016

  Gurgaon, India Developed an inventory forecasting model for there Superstore and Value store from scratch. ● Predicted the sale of a product for a particular store based on the historical sales data. ● Predicted the sale of a product with no data points. ● Calculated the normalizing factor at a Sub-Category level for normalizing the sale. ● Generated a purchase indent, based on the prediction, for a particular store. ● Automated the whole process. ● Language Used- Python . ● Tools… Show more Developed an inventory forecasting model for there Superstore and Value store from scratch. ● Predicted the sale of a product for a particular store based on the historical sales data. ● Predicted the sale of a product with no data points. ● Calculated the normalizing factor at a Sub-Category level for normalizing the sale. ● Generated a purchase indent, based on the prediction, for a particular store. ● Automated the whole process. ● Language Used- Python . ● Tools and Packages- Spyder, Panda,Tkinter. Show less