Dara Corr

I’m a Data Scientist with a first-class MSc in Data Science and BSc in Theoretical Physics, combining statistical rigour with hands-on work across cloud-based data environments and ML pipelines. I bring strong quantitative reasoning to predictive modelling, AI and machine learning, NLP, and time series analysis in both academic and industry settings.

In my Senior IT Engineering role on the Data Platform team at Advanced Micro Devices (AMD), I automated PostgreSQL, MySQL, and MongoDB database deployments using Python, cutting end-to-end install times by 90%. I engineered Snowflake cloud data pipelines processing >10 TB of data, optimizing query performance and reducing costs by $100K+ annually.

I also apply statistical methods to monitor database performance metrics, identify degradation signals, and surface operational risk indicators. I build ETL pipelines for data lake projects centralising auditing and security telemetry, enabling structured reporting on access patterns and anomalies, and I work closely with engineering and operations teams to optimize complex SQL workloads.

My academic and project work reflects the same focus on modelling and measurable outcomes: my MSc thesis used agent-based modelling of Mpox transmission dynamics, and I’ve built NLP pipelines in TensorFlow/NLTK for sentiment and text classification. I’ve also delivered anomaly detection with AUC-ROC of 0.997, option volatility analysis with Black-Scholes, and image classification for pneumonia using pre-trained neural networks—always pairing strong experimentation with practical deployment thinking.