Summary
Overview
Work History
Education
Skills
Timeline
BHASKAR JYOTI SAIKIA

BHASKAR JYOTI SAIKIA

London,UK

Summary

As a lead machine learning engineer at Accenture, Develop and deploy end-to-end data and ML pipelines for various clients in the banking and energy sectors. Use Python, PyTorch, TensorFlow, sklearn, Flask, Scala, Spark, and other tools to create and monitor scalable and robust ML models for financial and operational data also leverage cloud platforms such as GCP and AWS to ensure data integrity, security, and accessibility.

Overview

8
8
years of professional experience

Work History

LEAD MACHINE LEARNING ENGINEER

ACCENTURE
LONDON
05.2022 - Current
  • Developed end-to-end model deployment pipelines with ETL data ingestion to the data warehouse and implemented caching strategy techniques to optimize data access and model performance.
  • Managed and optimized data warehouses, to facilitate data access for analysts and data scientists.
  • Utilized SQL, NoSQL databases, and schema design techniques to ensure data consistency and efficiency.
  • Led a team for delivering Data Science solutions.
  • Productionized machine learning models in various cloud environments, including GCP Vertex AI and AWS sagemaker, enhancing efficiency through caching strategies Docker and Kubernetes.
  • Implemented real-time data streaming solutions using [Specific technologies like Apache Kafka or Pub Sub], enabling timely data processing.
  • Implemented CI/CD pipelines using Jenkins and Airflow.
  • Conducted A/B experiments to measure the impact of features and refined models based on experiment results.
  • Utilized Large Language Models (LLMs) to extract insights and enhance data analysis.
  • Authored and published a globally recognized MLOps whitepaper for Accenture.
  • Currently engaged in foundational work on GenAI models in AWS, harnessing Large Language Models (LLMs) to drive innovations in AI and ML.

SENIOR MACHINE LEARNING ENGINEER

QUANTEXA
LONDON
09.2019 - 05.2022
  • Developed end-to-end model and ETL data deployment pipelines for productionising models and rest APIs with best practices
  • Implemented and deployed CI/CD pipelines like Jenkins and MLOps pipelines with airflow
  • Visualised metadata of MLOps and ETL pipeline with Grafana
  • Developed applications using Docker, Kubernetes and helm charts
  • Requirements gathering from stakeholders and delivering desired results
  • Collaborated with cross-functional development teams to raise technical standards for ongoing projects.

Data scientist

QMUL
LONDON
09.2018 - 07.2019
  • Real-time face detection by a drone using deep learning, tensor-flow and integrating machine learning with mobile apps
  • Developed deep learning model for face detection and image prediction
  • Integrated and deployed machine learning model with apps and in AWS and GCP
  • Data Analytics Project:
  • Analysed the stock data and made the prediction using machine learning and deep learning algorithms
  • Used stock data from yahoo API, LSTM model with Keras and ADAM optimizer, for prediction of stocks AAPL, GOOGL
  • Tableau for pattern recognition
  • GitHub : https://github.com/bha6kar/DataAnalyticsProject.git
  • Twitter Sentiment Analysis: GitHub: https://github.com/bha6kar/twitter_scrubbing

SOFTWARE DEVELOPER

EDELWEISS
MUMBAI
01.2018 - 08.2018
  • Designed and developed schema data models for Fraud of Banking and saving cards
  • Developed database objects, including tables, views and materialized views using SQL
  • Coordinated statistical data analysis, design, and information flow
  • Keywords: web server, AWS, Java, Eclipse, VS Code, JavaScript, jQuery, HTML, Postgre SQL, git, Jenkins, TDD

SOFTWARE DEVELOPER

ATOS
MUMBAI
06.2015 - 01.2018
  • Writing robust code in Java for back end and JavaScript for the front end
  • Designed and developed schema data models for Fraud of Banking and saving cards
  • Developed database objects, including tables, views and materialized views using SQL
  • Coordinated statistical data analysis, design, and information flow
  • Keywords: web server, AWS, Java, Eclipse, VS Code, JavaScript, jQuery, Ajax, HTML, Postgre SQL, git, Jenkins, TDD

Education

Master of Science - Big Data Science

Queen Mary, University of London, London
08/2018 - 08/2019

Bachelor of Engineering - Computer Science

Sharda University, India
08/2011 - 06/2015

Skills

  • Statistical Analysis Tools: Python, SCALA, Big Data Processing, Hadoop, Airflow, Spark, Jupyter Notebook, Docker, Kubernetes
  • Machine Learning Framework: PyTorch, Tensorflow, Deep Learning, Scikit-learn, MLPack
  • Backend: Python, JavaScript, Flask
  • Cloud Computing: AWS Sagemaker, Google Cloud Platform (GCP) Vertex AI
  • Web Server related: Apache, Nginx, FTP, email, firewall, backup, system monitoring and security
  • Version Control: Git, SVN, CI
  • Database: Elasticsearch, MySQL, MongoDB, Oracle SQL, Postgre SQL
  • CERTIFICATES
  • Certification in Java by Oracle
  • (OCJP ~ 93 %)
  • Oracle SQL Associate Developer certification (OCA ~ 89 %)

Timeline

LEAD MACHINE LEARNING ENGINEER - ACCENTURE
05.2022 - Current
SENIOR MACHINE LEARNING ENGINEER - QUANTEXA
09.2019 - 05.2022
Data scientist - QMUL
09.2018 - 07.2019
SOFTWARE DEVELOPER - EDELWEISS
01.2018 - 08.2018
SOFTWARE DEVELOPER - ATOS
06.2015 - 01.2018
Queen Mary, University of London - Master of Science, Big Data Science
08/2018 - 08/2019
Sharda University - Bachelor of Engineering, Computer Science
08/2011 - 06/2015

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