Bangalore, India
Data Architect with 11 years of experience in machine learning, data pipelining, data
analytics/transformation and storage technology domain. Adept in designing and implementing
end-to-end data science projects. Loaded with a wide range of skill sets scaling from system
programming, protocol layer development, middleware development, infrastructure bring-up and
some presentation layer development. With innovation being the key strength and execution
equally complimenting can handle projects from start to finish.
English
sklearn, keras, tensorflow, pandas, numpy, flask
https://www.linkedin.com/in/biswapratap-chatterjee-42277518/
Data Architect with 11 years of experience in machine learning, data pipelining, data
analytics/transformation and storage technology domain. Adept in designing and implementing
end-to-end data science projects. Loaded with a wide range of skill sets scaling from system
programming, protocol layer development, middleware development, infrastructure bring-up and
some presentation layer development. With innovation being the key strength and execution
equally complimenting can handle projects from start to finish.
Experience
2017-03 -
present
Data Architect
Western Digital
QVisor
Jarvis
Optimaliseer
Log Analyzer
WD360- An Intra-Company Appathon Competition
Targeted for validation testing of Western Digital firmware using attention based
reinforcement learning.
Responsible from POC developments for early risk mitigation to full execution
of the project.
An intelligent agent for managing different datasets produced by various teams
across Western Digital.
Automatic relationship determination, relationship heatmap generation, auto-
highlighting of hidden interesting data correlation, 2D and 3D graph projections.
A reinforcement learning agent aiding Western Digital Drive firmware to
enhance performance.
Auto tuning of firmware configurable parameters to achieve enhanced
performance.
Achieved 12% performance improvement as compared to human (expert)
tuning.
An algorithm and machine learning based log analyzer for - Anomaly detection,
Parameter Extraction, Root Cause Analysis, Bug Classification.
Patent applied algorithm to auto cluster logs based on log structure and log
time.
Generate finite state machines from time based logs for debugging and root
cause analysis.
The search engine could search based on n-grams, context and objects
(images/audio/doc).
2015-03 -
present
Personal R&D for skill development
Skills
Machine Learning – a) Python –
Keras, Keras-RL, Tensor Flow. b)
Supervised Learning. a. Classification
Problems. b. Decision making
Problems. c) Reinforcement Learning:
a. Q-learning. b. Policy Gradient
Learning. c. Deep Deterministic Policy
Gradient (Actor-Critic) Learning. d)
Genetic Algorithm e) Attention Based
Neural Networks f) GANs g)
Unsupervised Learning h) NLP i) RNN
j) LSTM
advanced
Data Analytics – a) Infrastructure. a.
Spark/Mesos b. Elastic Search. c.
MongoDB. d. Scalable REST APIs
using Falcon. b)
Algorithms/Techniques. a.
Pandas/Numpy/SciPy/SkLearn etc. b.
Web Scrapping. c. Natural Language
Processing (NLP). d. Image Analytics
using OpenCV. e. Audio Analytics
using Sony GraceNote. f.
Document/Text/Emotion Analytics
using IBM Watson. g. Density
Distribution. h. Timeline Distribution. i.
Predictive Analysis. j. Decision Tree
Classifiers.
advanced
Storage Application Development
and Sustenance. a) Enterprise and
Consumer Grade. b) SMIS, SNIA,
CIM, OpenSSL, OpenSLP. c) SCSI,
SATA, NVMe, PCI protocol
development stack. d) RAID and
Initiator Target Storage Controllers.
advanced
System Application Development
(Windows, Linux, VMware) – a) C/C++
b) RESTful Applications. c) Python. d)
Android. e) Java. f) NodeJS/Electron
advanced
Self
All the projects mentioned below are personal projects or online competitions
done in private time in parallel with professional work.
Case Resolver
Buddy
Problem Statement: A company has more than 50,000 clients and there is a
dedicated Field Application Team (FAT) for each client. The FATs and the clients
communicate via various means like chat, email, Jira/bug tool etc. The FATs
and the clients sometimes do not use grammatically correct English sentences
for their communication. Moreover the FAT often mentions the name of the
same client in various forms like - IBM, IBM Pvt. Ltd., IBM Corp, IBM Global etc.
The company wants to segregate all communications by unique client names
and also figure out the accurate date for a case to have resolved from the
discussions between the FATs and the clients.
Problem was solved using algorithms, supervised ML, Natural Language
Processing, Sentiment Analysis and Regular Expressions.
We spend a lot of time browsing over the internet in e-commerce websites over
millions of products on a daily basis. Still we are never sure if we made the best
choice, not just w.r.t. price but personal choice (which can be many).
This ML agent solves this problem of the user using - algorithms, web
scrapping, genetic algorithms etc.
2016-09 -
2017-03
Senior Firmware Developer
Seagate
Dothill
This project was about the sustenance of the well-known product – Dothill
Storage Array. The storage array was used to address the mid-range of the array
market with various features involving SATA and SAS drives. The project required
me to work on the sustenance roadmap of the Dothill storage array. I worked in
the night US shift to address high priority customer issues by analysing Firmware
logs and providing recovery or code fix action plans. I was involved in multiple
modules of the product from – Platform, Backend, RAID, Cache, Paged Storage,
Snapshot and Tiering.
2015-06 -
2016-09
Senior Staff
Broadcom
Management Stack of 1G, 10G and 50G Network Controllers
The project involves the development and maintenance of the software
management stack for high end network controllers from Broadcom. I am acting
as a prime engineer in designing and implementing the entire stack. I have
complete knowledge on the stack starting from the CLI, CIM till the OS library.
2013-03 -
2015-06
Staff Engineer
Sandisk
Projects related to storage protocols like - SATA, SCSI, NVMe
2008-09 -
2013-03
Senior Software Engineer
Wipro
Projects related to storage protocols like - SATA, SCSI, NVMe, RAID
Web Application Development – a)
AngularJS 4+ b)
JavaScript/JQuery/TypeScript/HTML/
CSS
hands on
Search Engine Development.
average
Android Application Development
in Java.
hands on
Education
2004-05 -
2008-05
Kalinga Institute of Industrial Technology (KIIT) University
Artificial Intelligence (AI), Big Data, Data Science, Elasticsearch, Machine Learning, Natural Language Processing