Hi, I am Saurabh

This is my portfolio website.
I like technical writing and programming.
I love working on fun projects.

Saurabh Jain

Data Scientist at Siemens Technology and Services

My job involves working on Data Science projects. Some of them are strategic while othere are customer facing. Other than working on projects, I try to be active in guilds where we discuss upcoming technologies and how they can benefit Siemens.

I see technologies and tools as a means to achieve business goals and not as an end in itself. I believe in continous learning and improvement. My blogs are based on the things that I am doing or learning; they will serve me or others for reference in future.

Leadership

Team Work

Communication

Hard Work

Fast Learner

Problem Solving

Tech Stack

Python

Using as the main language for professional development. Capable of writing scalable, testable, and maintainable program.

Cloud Computing

Worked with most of the major clouds such as GCP, AWS, Azure etc.

Git

Experienced with git-based environment. Mostly use, Github. Also, have experience in working with Gitlab.

R

Primary tool for doing Data Analysis and Visualization.

Machine Learning

Standard tool for developing most of the Machine Learning applications.

Deep Learning

Comfortable in using Pytorch and Tensorflow/ Keras for developing deep learning applications.

Docker

Writing applications in dockerized containers so that sharing and deployment becomes easy.

UiPath

Worked on couple of RPA projects that involved UiPath. Developed and orchestrated the project workflow.

Recent Posts

Reflections from SITEX 2021

SITEX stands for SIEMENS Innovation and Technology Exchange. Its a program which focuses on developing PoC around strategically identified Technologies. Employees around the globe participate, form teams and pitch their usecase to the jury which comprises of Heads of several departments. So this is a huge event with a lot of visibility. The technologies identified for the year 2021 were: Mendix Edge Computing Computer Vision Demand Forecasting Hololayer Industrial 5G I was part of Computer Vision team.

June 26, 2021 Read

Personalized Cancer Diagnosis

Problem Statement: Classify the given genetic variations/mutations based on evidence from text-based clinical literature. Details: https://www.kaggle.com/c/msk-redefining-cancer-treatment/ https://www.kaggle.com/c/msk-redefining-cancer-treatment/discussion/35336#198462 Real-world/Business objectives and constraints No low-latency requirement. Interpretability is important. Errors can be very costly. Probability of a data-point belonging to each class is needed. Data Data Overview Source We have two data files: one conatins the information about the genetic mutations and the other contains the clinical evidence (text) that human experts/pathologists use to classify the genetic mutations.

August 31, 2019 Read

Social Network Graph Link Prediction

Details: https://www.kaggle.com/c/FacebookRecruiting/data Problem Statement: Given a directed social graph, have to predict missing links to recommend users (Link Prediction in graph). This case study takes lot of references from graph theory. Purely graph based link prediction. Undirected graph: connection from both edge. (eg. Fb friends) Directed graphs: connection from one direction. It can be from both directions. (eg. Twitter/IG following) A path is a sequence of edge that you follow to reach from edge e1 to edge e5.

August 12, 2019 Read