Curriculum Vitae · Dr. Jeremy Rigney

From stellar physics to production AI

Senior Data Scientist · AI R&D · Astrophysicist

A PhD physicist turned data scientist — building large-scale data pipelines and models, with a decade of Python and a research record spanning international, peer-reviewed astrophysics.

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PhD 2024 Astrophysics, QUB
6 Publications
3 Awards
8+ Years of Python

Roles Publications

01 / Experience

A few places my work lives.

2026 to present

Optum

Senior Data Scientist

  • AI R&D: designing and deploying agentic systems for production use.
  • Building and evaluating LLM-based pipelines, from prototype through to deployment.
  • Production ML models in a regulated healthcare data environment.
2025 to 2026

LexisNexis Risk Solutions

Data Scientist

  • Vehicle data: risk models and analytics over large-scale vehicle datasets.
  • Feature engineering and validation on high-volume records.
  • Production Python, SQL and cloud ETL.
2020 to 2024

Queen’s University Belfast

PhD Researcher

  • Designed and operated high-throughput data pipelines processing >100TB of time-series data from multi-instrument sensor arrays.
  • Managed real-time data acquisition as Chief Observer, overseeing streams of up to 3 GB/s with a focus on data integrity, storage, and downstream signal processing.
  • Engineered feature extraction and anomaly detection systems to identify rare signals in high-noise environments.
  • Implemented parallelised, containerised workflows (Slurm, Singularity) to ensure repeatable, audited data processing in high-compute environments.
  • Validated complex models by comparing simulated datasets against empirical measurements.
  • Award-winning science communicator, recognised for translating highly technical astrophysical and mathematical concepts for diverse, non-specialist audiences.

02 / Education

Where it was built.

2020 to 2024

Queen’s University Belfast

Doctorate of Philosophy — Astrophysics

School of Mathematics and Physics.

2016 to 2020

University College Dublin

BSc (Hons) — Physics with Astronomy & Space Science

  • Relevant coursework: Probability and Statistics, Databases and Information Systems (SQL), Applied Mathematics, Linear Algebra, Calculus.

03 / Technical skills

The toolkit.

  • AI & Machine Learning

    Large Language Models (LLMs), applied ML for anomaly detection and signal classification.

  • Programming

    Python (8+ years), SQL (Advanced), Bash, R.

  • Data Engineering

    Azure, AWS, high-volume ETL, Parquet, batch & stream processing.

  • Specialised Analysis

    Time-series signal processing, sensor fusion, multi-channel data analysis.

  • Privacy & Security

    Data anonymisation / de-identification, GDPR-compliant data design.

  • Software Practices

    Production-grade Python (PEP8, type hinting, docstrings), modular design, unit testing (PyTest), CI/CD, Docker, Git-flow.

04 / Awards

Recognition.

  • 2024

    Institute of Physics Three-Minute Wonder UK & Ireland Audience Award — Royal Institution, London, United Kingdom.

  • 2024

    IOP Rosse Medal for Best Postgraduate Presentation — IOP Irish HQ, Dublin, Ireland.

  • 2022

    Peter Curran Award for Best Postgraduate Presentation — Irish National Astronomy Meeting, Dublin, Ireland.

05 / Publications

Peer-reviewed research.

  • 01 PhD Thesis · 2024

    Multiwavelength observations of flaring activity on the Sun and M dwarf stars

    Jeremy Rigney · Queen’s University Belfast

  • 02 Nature Astronomy · 2024

    Radio signatures of star–planet interactions, exoplanets and space weather

    Callingham J. R., Pope B. J. S., Kavanagh R. D., Bellotti S., Daley-Yates S., Damasso M., Grießmeier J.-M., Güdel M., Günther M., Kao M. M., Klein B., Mahadevan S., Morin J., Nichols J. D., Osten R. A., Perez-Torres M., Pineda J. S., Rigney J., Saur J., Stefánsson G., Turner J. D., Vedantham H., Vidotto A. A., Villadsen J. & Zarka P.

  • 03 Astronomy & Astrophysics · 2024

    Tracking the motion of a shock along a channel in the low solar corona

    Jeremy Rigney, Peter T. Gallagher, Gavin Ramsay, J. Gerry Doyle, David M. Long, Oleg Stepanyuk, Kamen Kosarev

  • 04 MNRAS · 2022

    Searching for stellar flares from low-mass stars using ASKAP and TESS

    Jeremy Rigney, Gavin Ramsay, Eoin P. Carley, J. Gerry Doyle, Peter T. Gallagher, Yuanming Wang, Joshua Pritchard, Tara Murphy, Emil Lenc, David L. Kaplan

  • 05 Astronomy & Astrophysics · 2021

    First results from the REAL-time Transient Acquisition backend (REALTA) at the Irish LOFAR station

    P. C. Murphy, Paul Callanan, J. McCauley, D. J. McKenna, D. Ó Fionnagáin, C. K. Louis, M. P. Redman, L. A. Cañizares, E. P. Carley, S. A. Maloney, B. Coghlan, Mark Daly, J. Scully, J. Dooley, V. Gajjar, C. Giese, A. Brennan, E. F. Keane, C. A. Maguire, J. Quinn, S. Mooney, A. M. Ryan, J. Walsh, C. M. Jackman, A. Golden, T. P. Ray, J. G. Doyle, J. Rigney, M. Burton, P. T. Gallagher

  • 06 IT&T Proceedings · 2014

    Comparing Game Based Learning, using a student created game, to Traditional Classroom Methods

    Jeremy Rigney, Niall Murray

06 / Get in touch

Let’s talk data, research, or a talk.

I welcome opportunities to engage in public speaking — particularly at science festivals, open days and similar events — as well as data and research collaborations. Feel free to reach out.