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Sagar Toms

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About Me

I am Sagar Toms. I am currently working as an Applications Engineer at Oracle India Pvt. Ltd. I have a combined experience of 3.5+ years predominantly in Python, Java and Data Engineering. I represent myself as a quick learner and can work irrespective of the technology stack.

About my education, I have a Master's degree in Information Security from College of Engineering Trivandrum (Kerala, India) and Bachelor's degree in Computer Science and Engineering from Cochin University of Science and Technology (Kerala, India).

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Experience

Oracle India Private Limited

Applications Engineer

Oracle Service Cloud

  • Designed, implemented and deployed an end-to-end system for a context based text generation using Machine Learning.
  • Debugged and implemented fixes for high priority defects within a stipulated time frame irrespective of technology stack. Created unit test cases to cover edge scenarios.
  • Implemented and delivered features for the product by collaborating with various teams.
  • Proactively monitored CI/CD pipelines and reported the failures.
  • Prepared technical documentations and worked closely with documentation team to publish the material.
  • Actively participated in code reviews to learn and understand about the best practices and coding standards followed in the organization.
  • Technologies: Python, Java, Javascript, Typescript, HTML, CSS, Docker, Kubernetes, Oracle Cloud Infrastructure (OCI).

Infosys Limited

Senior Systems Engineer

Data Engineering Team

  • Experience on the end-to-end implementation of Data Warehouse for a fortune 500 logistics major.
  • Developed Azure ADF data pipelines to move data from on-premise system to Azure SQL Data Warehouse
  • Developed Azure automation scripts to automate the resource management which reduced the overall costs.
  • Experience in generating ARM templates and its deployment to higher environments.
  • Developed Azure Databricks notebooks for near real-time data processing and reporting.
  • Technologies: Microsoft Azure Data Factory, Databricks Notebook, MS SQL, SSIS, Power BI, Python

Infosys Limited

Systems Engineer

Big Data Centre of Excellence (CoE) Team
  • Experience in Python and Apache Spark especially in near real-time development.
  • Developed a machine learning endpoint for a big data real-time streaming framework using PySpark code which enables users to apply machine learning algorithms on real-time streaming data.
  • Configured load balancing on Python Flask uWSGI Server and Plumber in R to enable high throughput for applying machine learning algorithm on streaming data.
  • Developed an ad-hoc reporting tool based on Python (Flask-SQLAlchemy), HTML5 and JavaScript(Chart.js, D3.js), which plots static visualizations based on REST API calls. Implemented custom caching layer for caching the datasets which provides better performance than parquet files.
  • Created SQL scripts to automate the repetitive tasks which drastically reduced the development time.
  • Technologies:Python Flask, SQLAlchemy, Pandas, HTML5, JavaScript

Infosys Limited

Systems Engineer Trainee

  • Trained in Python and SAP ABAP from Infosys Global Education Centre,Mysore.Scored as High Performer(HPF).

Education

College of Engineering Trivandrum

Sep 2019 - Jun 2021

Master of Technology (M. Tech) in Computer Science and Engineering

College of Engineering Kallooppara

Sep 2012 - May 2016

Bachelor of Technology (B. Tech) in Computer Science and Engineering

Technical Higher Secondary School Mallappally

Jun 2010 - Mar 2012

Higher Secondary (Class XII)

SBHSS Vennikulam

Mar 2010

High School (Class X)

Projects

Real-time IoT Botnet Attack Detection using Deep Learning Technique

Project work done as part of M. Tech course. Implemented a deep learning model trained with Bot-IoT dataset to detect botnet attacks in IoT smart home networks. The system works by monitoring the network in real-time and shows a real-time dashboard to the network administrator including the details about network traffic, possible attacks etc.

Real-time Cyber Attack Detection System Using Machine Learning Techniques

Developed a decision tree based machine learning model, trained using UNSW-NB15 dataset that can classify real-time network traffic as attack traffic or normal traffic. The real-time traffic data and classification results are plotted using Grafana dashboard.

Snotes: Simple Secure Notes

A python package for encrypting and storing notes in SQLite DB.

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Skills

Certifications

Python (Basic)

May 2020, by HackerRank

It covers topics like Scalar Types, Operators and Control Flow, Strings, Collections and Iteration, Modularity, Objects and Types and Classes.

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Problem Solving (Basic)

May 2020, by HackerRank

It covers basic topics of Data Structures (such as Arrays, Strings) and Algorithms (such as Sorting and Searching).

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Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

May 2020, by Coursera

Helped to learn best practices for using TensorFlow, a popular open-source machine learning framework

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Google Cloud Platform Big Data and Machine Learning Fundamentals

May 2020, by Coursera

Helped to learn processing big data at scale for analytics and machine learning.

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