Siddharth Gangrade

I joined SAP as an Intern as an ally of the Autism at work program in July 2019. Since I Joined Along with Contributing to SAP's objectives, I have been also provided with a support system which has enable me to build myself into a much much better version of myself. Something I would not have even thought of while joining.

To Know more about me you can go through the following -

https://blogs.one.int.sap/labsindianews/2023/04/17/looking-through-a-chaotic-yet-orderly-mind/

MLops Specialization from DeepLearning.Ai

Developed proficiency in gathering, cleaning, and validating datasets to build robust data pipelines essential for ML model training and deployment. Emphasized the importance of data lifecycle management to ensure data quality and integrity.

Explored methods for monitoring model performance, detecting anomalies, and implementing proactive measures to maintain the health and reliability of ML models in production.

Learned best practices and progressive delivery techniques for maintaining and monitoring continuously operating ML production systems.

JUNE 2014

Cleared the JEE Advanced Exam with an all India rank of 2077 conducted by IIT Kharagpur

AUGUST 2020

Winner of LOB award under Rising Star Category at S4/HANA Test engineering Annual Awards

JULY 2023

Runner-up in a globally held hackathon at the organizational level focused on Generative AI technology, presenting a pioneering use case titled "Using GenAi to Directly Generate Automation from Test Documents."

Satellite Image Processing Through Machine Learning Algorithms OCTOBER 2017- JANUARY 2018

• Learnt to deploy machine learning algorithms directly in python.
• Learnt to use different machine learning libraries in python.
• Github - https://github.com/rpsg35/SIMG-project

Simple Effort Logging Tool Development FEB 2020 - DECEMBER 2020

• Github - https://github.wdf.sap.corp/I519129/Easy-Effort-Logging-Tool
• Full Stack Development of a Weekly Planning Tool currently under use by my Team.
• Actions in tool are reflected in JIRA via API calls.
• Used flask framework for API and backend calls.
• Used HTML5 , Jquery, ajax for frontend Development.
• Test Case Prioritization Through Deep reinforcement Learning OCTOBER 2021 - Feb 2022

• Machine Learning - Model Training and Development using Policy Gradient Learning based algorithm for Prioritizing test cases based on historical data and customer usage Data.
• Used Tensorflow to train and run algorithms. Concept was Runner up in MLGathon'21 by Innovati’O’ @ STE.