Nishant Yadav

Associate Technical Lead at Flutura Decision Sciences & Analytics
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Contact Information
us****@****om
(386) 825-5501
Location
Bengaluru, Karnataka, India, IN

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Credentials

  • Learning Data Governance
    LinkedIn
    May, 2021
    - Nov, 2024
  • Learning Terraform
    LinkedIn
    Mar, 2021
    - Nov, 2024
  • Apache Flink: Batch Mode Data Engineering
    LinkedIn
    Sep, 2020
    - Nov, 2024
  • Big Data Foundations - Level 1
    IBM
    Sep, 2019
    - Nov, 2024
  • Big Data Foundations - Level 2
    IBM
    Sep, 2019
    - Nov, 2024
  • Hadoop 101
    IBM Cognitive Class
    Sep, 2019
    - Nov, 2024
  • Hadoop Foundations - Level 1
    IBM
    Sep, 2019
    - Nov, 2024
  • Simplifying Data Pipelines with Apache Kafka
    IBM Cognitive Class
    Sep, 2019
    - Nov, 2024
  • Spark - Level 1
    IBM
    Sep, 2019
    - Nov, 2024
  • Spark Fundamentals I
    IBM Cognitive Class
    Sep, 2019
    - Nov, 2024

Experience

    • United States
    • Software Development
    • 100 - 200 Employee
    • Associate Technical Lead
      • Apr 2023 - Present

    • Senior Programmer - Data Engineering
      • Apr 2021 - Mar 2023

    • Programmer - Data Engineering
      • Nov 2019 - Apr 2021

    • Trainee- Programmer
      • Jul 2019 - Oct 2019

    • Project: Data Driven Intelligent Public Transportation Using LoRa
      • Mar 2019 - Jul 2019

      This project was focused at proposing new solution for public transport tracking systems with the use of IoT and Dynamic Scheduling of Buses based on data leveraged from Electronic Ticketing Machines (ETMs). Tracking of Buses in Real-time: The buses will be equipped with LoRa transceiver, which sends out data regarding the bus identity, bus route and bus location to LoRa Gateways which in turn sends the data to cloud. LoRaWAN offers a wide range connectivity (Range can extend up to 5 to 10 km) while still providing a long battery life. Dynamic Scheduling: Used Electronic Ticketing Machine's data to accurately determine past trend of total passengers present across various bus stops at a given time of the day. Build machine learning model with use of K-Mean Algorithms and dynamic clustering procedures to forecast the best Schedules for the BMTC buses in real time. This helped in achieving following: - Mapping origin-destination trends of passengers and identifying busy bus-stops and buses, and leverage this information to identify optimized schedules for the buses. - Better coverage area for the buses. - Reducing overcrowding of the buses. - Exploring the possibility for using real-time data to determine passenger-waiting time in order to enhance the efficiency of the bus dispatching system. Show less

    • United States
    • E-Learning Providers
    • 1 - 100 Employee
    • Data Science Intern
      • Jan 2019 - Mar 2019

      Worked on Google of Learning(GOL), with primary focus to measure and assess person's learning based on continuous goal based learning approach. Used Slack messaging platform, and build GOL Bot to leverage sharing of learning across peers. Generated weekly reports based on their learning posted on slack and peers involvement on the same. Got experience in AWS Lambda for Server-less architecture and Text based Data Analysis. Worked on Google of Learning(GOL), with primary focus to measure and assess person's learning based on continuous goal based learning approach. Used Slack messaging platform, and build GOL Bot to leverage sharing of learning across peers. Generated weekly reports based on their learning posted on slack and peers involvement on the same. Got experience in AWS Lambda for Server-less architecture and Text based Data Analysis.

Education

  • Sapthagiri College of Engineering Bengaluru, Affiliated to Visvesvaraya Technological University
    Bachelor of Engineering - BE, Computer Science
    2015 - 2019
  • Kendriya Vidyalaya Hebbal, Bengaluru
    Secondry Education
    2010 - 2015

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