I am a Lead Data Scientist with 8 years of experience delivering industry-leading solutions in private healthcare markets to support business revenue and investment. I led the development of two FDA 510(k) clearances for automated ECG analysis using machine learning, with products deployed on embedded devices and cloud platforms for the U.S. healthcare market. I’ve designed and implemented a scalable ML platform on GCP with modern MLOps practices, including experiment tracking, version control, and model monitoring. I have a track record of building multi-agent AI systems, with knowledge of Foundation Model architectures, RAG, fine-tuning, data engineering, LangChain, and CrewAI. I’ve presented research at the American Heart Association conference in 2024 and have hands-on experience delivering Computer Vision solutions in Digital & Computational Pathology for cancer detection and bioinformatic pipelines.…

Adrian Deery

I am a Lead Data Scientist with 8 years of experience delivering industry-leading solutions in private healthcare markets to support business revenue and investment. I led the development of two FDA 510(k) clearances for automated ECG analysis using machine learning, with products deployed on embedded devices and cloud platforms for the U.S. healthcare market. I’ve designed and implemented a scalable ML platform on GCP with modern MLOps practices, including experiment tracking, version control, and model monitoring. I have a track record of building multi-agent AI systems, with knowledge of Foundation Model architectures, RAG, fine-tuning, data engineering, LangChain, and CrewAI. I’ve presented research at the American Heart Association conference in 2024 and have hands-on experience delivering Computer Vision solutions in Digital & Computational Pathology for cancer detection and bioinformatic pipelines.…

Available to hire

I am a Lead Data Scientist with 8 years of experience delivering industry-leading solutions in private healthcare markets to support business revenue and investment. I led the development of two FDA 510(k) clearances for automated ECG analysis using machine learning, with products deployed on embedded devices and cloud platforms for the U.S. healthcare market.

I’ve designed and implemented a scalable ML platform on GCP with modern MLOps practices, including experiment tracking, version control, and model monitoring. I have a track record of building multi-agent AI systems, with knowledge of Foundation Model architectures, RAG, fine-tuning, data engineering, LangChain, and CrewAI. I’ve presented research at the American Heart Association conference in 2024 and have hands-on experience delivering Computer Vision solutions in Digital & Computational Pathology for cancer detection and bioinformatic pipelines.

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Work Experience

Lead Data Scientist at B-Secur
March 1, 2018 - February 1, 2026
Delivered 2 FDA 510k clearances for automated ECG analysis algorithms, leading end-to-end development from clinical & market requirements gathering through algorithm development, validation, regulatory submission, and market clearance. Architected & implemented post-market surveillance system with automated distribution shift monitoring to ensure FDA compliance and early detection of model degradation. Designed end-to-end ML infrastructure including a GCP data lake, MLflow for experiment tracking, and DVC for data version control. Led clinical validation studies across thousands of patients, coordinated with cardiologists, and produced evidence for FDA submissions. Built a Gemini-powered natural language query interface for a clinical data lake to enable non-technical stakeholders to query datasets in natural language. Collaborated with CTO and Head of Product to shape product roadmap and translated clinical needs into technical requirements. Allocated 10-20% of time to develop and val
Data Scientist at Sonrai Analytics
October 1, 2021 - March 1, 2022
Led the algorithm development of a deep learning system using computer vision to identify microsatellite instability (MSI) in H&E stained whole slide images (WSI) for colorectal cancer pathology. Worked with NHS cohorts, AWS S3 for large image data, PyTorch, multiple instance learning, and HPC for parallel training. Presented to NHS patient groups to gather feedback and educate on AI in medicine. Developed the statistical framework and power analysis for a CE Class IIB submission, including non-inferiority testing against gold standards.

Education

MSc in Bioinformatics and Computational Genomics at Queen's University Belfast
September 1, 2021 - September 1, 2022
BSc in Mathematics and Statistical & Operational Research at Queen's University Belfast
September 1, 2014 - June 1, 2017
MSc in Bioinformatics and Computational Genomics with Distinction at Queens University, Belfast, UK
September 1, 2021 - September 1, 2022
BSc in Mathematics and Statistical & Operational Research with First Class Honours at Queens University, Belfast, UK
September 1, 2014 - June 1, 2017
MSc in Bioinformatics and Computational Genomics at Queen's University Belfast
September 1, 2021 - September 1, 2022
BSc in Mathematics and Statistical & Operational Research at Queen's University Belfast
September 1, 2014 - June 1, 2017

Qualifications

ACS Skills Assessment
January 11, 2030 - March 27, 2026
ACS Skills Assessment
January 11, 2030 - April 21, 2026
ACS Skills Assessment
January 11, 2030 - April 21, 2026

Industry Experience

Healthcare, Life Sciences, Professional Services, Software & Internet
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    Automate the structured data extraction and meta-analysis from study PDFs as part of a systematic review workflow. Evaluate the optimal combination of AI agents, NER, Python Libraries and REGEX.

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