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Shashank Kumar

Bis 2018, Senior Systems Engineer, Infosys Ltd.
Siegen, Deutschland

Fähigkeiten und Kenntnisse

Python
Java
PySpark
Computer Vision
Machine Learning
Natural Language Processing (NLP)
GitHub
MySQL
SQLAlchemy
Softwareentwicklung
Spring
Spring Boot
Agile scrum methodology
Git
Natural language processing
Apache Spark
Docker
AWS Lambda
AWS EC2
Hibernate
Deep Learning
Flask
MicroServices

Werdegang

Berufserfahrung von Shashank Kumar

  • 8 Monate, Jan. 2018 - Aug. 2018

    Senior Software Engineer (Data Engineer)

    Infosys Limited
  • 3 Jahre und 4 Monate, Mai 2015 - Aug. 2018

    Senior Systems Engineer

    Infosys Ltd.

    • Involved as a Python developer, developing and maintaining applications. • Used Flask framework to build prototype website which connects with the SQL database using SQLAlchemy. • Developing and maintaining the application backend RESTful API. • Also involved as a Java developer, involved in requirements gathering, analysis, design, and documentation of the application. • Developed services using Hibernate, RESTful services with good quality code. • Developed MySQL scripts.

  • 2 Jahre und 3 Monate, Okt. 2015 - Dez. 2017

    Senior Software Engineer (Python developer)

    Infosys Limited

Ausbildung von Shashank Kumar

  • 8 Monate, Dez. 2020 - Juli 2021

    Mechatronics, Systems Engineering

    University of Siegen, Germany

    • Textual data mining for root cause analysis of industrial data by comparing state of the art clustering approaches and key-phrase extraction algorithms. • Implemented semantic search model using BERT to extract semantically similar documents. • Prepared sample dataset for evaluation and testing of similarity and key-phrase extraction algorithms. • Created a Python/Flask based web application using Python scripting for data processing and developed application backend RESTful APIs.

  • 10 Monate, März 2020 - Dez. 2020

    Mechatronics, Systems Engineering

    University of Siegen, Germany

    • Camera based Surgical navigation system: Deep learning-based approach for classification and detection of X-Markers. • Classification & detection of X-Markers using pre-trained and custom networks. • Dataset generation and annotation with image calibration. • Fine-tuning and training of pre-trained object detection algorithms.

  • 2 Jahre und 11 Monate, Sep. 2018 - Juli 2021

    Mechatronics, Systems Engineering

    University of Siegen, Germany

Sprachen

  • Englisch

    Fließend

  • Deutsch

    Grundlagen

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