Shalmoly Mondal
Melbourne,Australia
Summary
Experienced Data Engineer with a strong foundation in data analysis and software development, specializing in building scalable data pipelines and optimizing ETL processes. Proven ability to work with streaming data, leveraging statistical analysis, and machine learning techniques. Adept at using tools like Python, SQL, and cloud platforms to extract insights and drive business decisions. Seeking to transition into Data Scientist roles where I can apply my expertise in data engineering and analysis to solve complex, real-world problems using machine learning and advanced analytics.
Overview
7
7
years of professional experience
1
1
Certification
Work History
RND SOFTWARE DEVELOPER
BlueIoT
Mulgrave, Australia
08.2023 - 11.2023
- Designed and built interactive air quality monitoring dashboards using React.JS, enhancing UI/UX which boosted user engagement by 30% and reduced response time
- Transformed raw sensor data from 8 sources into actionable insights through Exploratory Data Analysis (EDA) using Excel and Python libraries, resulting in a 22% improvement in data accuracy
- Created interactive visualizations to communicate insights to stakeholders, increasing data comprehension by 15%
- Established and managed databases using SQL queries on Amazon Timestream and DynamoDB, reducing data retrieval time by 40%.
IOT RESEARCHER
Swinburne University of Technology
, Australia
05.2019 - 06.2023
- Designed and implemented a comprehensive framework to automate data generation for IoT applications, enhancing research efficiency
- Analyzed large datasets to generate synthetic data, employing statistical techniques to identify key patterns and trends across over 10,000 data points.
ORACLE APPS - SQL DEVELOPER
Infosys Limited
Hyderabad, India
03.2017 - 03.2019
- Leveraged PL/SQL to efficiently extract, transform, and load data across 10+ development projects
- Developed and maintained complex PL/SQL procedures to automate data cleaning in Oracle, reducing data processing time by 10%
- Created logical and technical documents to streamline the development process, reducing development time by 13%
- Achieved a 100% on-time delivery rate by collaborating effectively with cross-functional teams.
Education
Ph.D. - Computer Science
Swinburne University of Technology
Melbourne, Victoria06.2023
M.Tech - Computer Science
IIT (ISM)
Dhanbad, Jharkhand05.2016
B.Tech - Computer Science
Calcutta Institute of Technology
West Bengal, India06.2014
Skills
- Programming Languages: PL/SQL, T-SQL, Python, R
- Databases: SQL Server, Oracle, MongoDB
- Advanced Analysis : EDA, Time-series analysis, Statistical analysis
- Cloud Platforms : Amazon Web Service (AWS), Microsoft Azure
- Data Engineering: Pipeline Development, ETL Operations, Data Warehousing
- AI and ML: Feature Engineering, Model Evaluation, Dimension Reduction, Computer Vision
- Data Visualisation: Matplotlib, seaborn, d3js
- Version Control: Git, GitHub
- Collaboration: Agile Methodology, Cross-functional Teamwork, Client Interaction, Technical Documentation
- Soft Skills: Critical Thinking, Problem Solving, Project Management, Time Efficiency, Organizational Skills, Effective Communication
Certification
- AWS Certified Cloud Practitioner Certificate, 01/01/20
- AWS Academy Accredited Educator, 01/01/20
- IBM Data Science Professional Certificate, Coursera, Ongoing
Projects
Activity Recognition in Smart Manufacturing: Developed a machine learning-based activity recognition system for a smart manufacturing IoT application.
- Leveraged Support Vector Machines (SVM) and Random Forest algorithms to accurately classify diverse activities of factory workers within the manufacturing process
- Achieved 77% classification accuracy, significantly contributing to the overall success of the smart manufacturing project
Bicycle Lane Detection: Developed a deep learning-based bicycle lane detection system for night-time driving.
- Analyzed real-time data streams from Nerian stereo vision depth cameras, processed approx. 140 hours of video.
- Implemented deep learning models and computer vision techniques to achieve 77% accuracy in bicycle lane detection under challenging night-time conditions
- Reduced false positives by 11%
Face Recognition System: Developed a high-accuracy face recognition system using eigenfaces and a distance classifier, achieving a recognition accuracy of 93.33%.
- Leveraged advanced image processing and statistical pattern recognition techniques in MATLAB to extract relevant features for image processing
- Implemented Principal Component Analysis (PCA) to further improve feature extraction, resulting in a 16% increase in overall accuracy
Timeline
RND SOFTWARE DEVELOPER
BlueIoT
08.2023 - 11.2023
IOT RESEARCHER
Swinburne University of Technology
05.2019 - 06.2023
ORACLE APPS - SQL DEVELOPER
Infosys Limited
03.2017 - 03.2019
Ph.D. - Computer Science
Swinburne University of Technology
M.Tech - Computer Science
IIT (ISM)
B.Tech - Computer Science
Calcutta Institute of Technology
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