dattatreya majumdar

Designed ML and AI project plans for forecasting insurance claims using geospatial data inputs. Built proof-of-concept solutions for customer and property analytics using large language model endpoints.

Applied machine learning and pattern recognition techniques for real-time track condition monitoring. Used RandomForest, XGBoost, and LLM-based approaches to support predictive maintenance for critical rail assets.

Developed time-series forecasting models for water consumption and revenue using Python, ARIMA, and SARIMA. Built deep learning solutions with TensorFlow and Keras using LSTM and GRU architectures for process optimisation.

Defined and coordinated data science workstreams for asset health maintenance and digital twin projects. Analysed maintenance records with Python-based NLP techniques and developed Power BI dashboards to identify critical assets and review MTBF.

Analysed high-frequency synchrophasor data from multiple Australian locations using Azure Virtual Machines and openHistorian, with results visualised in Grafana dashboards. Built automated data processing pipelines for electrical power quality analysis using pandas, NumPy, and openHistorian data sources.

Built Power BI and Grafana dashboards using historian and visualisation data to compare plant feed rate variation across four mine sites in New South Wales. Developed statistical models in R and Python to optimise plant feed rate fluctuations in mining operations.

Published monthly QA performance metrics and reported quarterly progress against organisational goals. Performed data quality validation and ETL/ELT testing across multiple platforms.

Master of Data Science degree from the University of Queensland, completed from 2019 to 2020.

Master of Technology in Electrical Engineering from the Indian Institute of Technology Madras, completed from 2014 to 2016.

Integrated Master of Science in Physics from the Integrated Science Education and Research Centre, Visva-Bharati, completed from 2009 to 2014.