Worked directly and collaboratively with business clients on a range of consulting projects, including:• Texas InstrumentsContributed to the development of a proof of concept using millimetre-wave radar technology for remote sensing. Performed statistical and image analysis to support project decision-making.• Child Mind InstituteEngineered a machine learning algorithm to detect and monitor body-focused repetitive behaviours such as trichotillomania, excoriation, and onychophagia. Contributed to the development of a wrist-worn monitoring device that enables healthcare professionals to effectively track treatment outcomes. Oversaw data collection methods and hardware choices, proactively identified project risks, and facilitated seamless execution through effective team communication.• Merck Sharp & DohmeEntrusted with defining the optimal features of an email marketing campaign using insights from the analysis of data captured with neuromarketing software.• London Stock Exchange GroupDevised, developed, and maintained software in R and Python to anonymise Personal Identifiable Information (PII) data, aligning with EU GDPR data protection and privacy laws. This initiative safeguarded a critical $250 million per annum revenue stream for the client. The software ingests, cleans and analyses the data and uses machine learning to generate a synthetic dataset that is structurally and statistically analogous but with robust privacy protections for use in non-production environments. Instituted best practice guidelines to aid the client in meeting GDPR commitments.

Affilated with CERN via the Wigner Research Center for Physics, California State University Fresno, Indiana University, and Royal Holloway University of London.A CERN User is a person who comes from, and is employed by, an outside institute to participate in an experiment at CERN and is authorised to access the facilities and resources of CERN for scientific research purposes. About 80% of people who work on experiments at CERN are guest scientists and engineers, known as Users, who are not directly employed by CERN.

Long-term attachment to CERN to work on the ATLAS experiment at the Large Hadron Collider as part of my PhD research.

Performed data analysis in R and C++ for the ALICE experiment at CERN, which recreates conditions that are believed to have existed a fraction of a second after the Big Bang. Used machine learning to develop classification algorithms for recognising particles based on their decay properties. Engaged with the data science community via public outreach talks and conference presentations.

Systematically investigated the potential benefit of hundreds of different predictor variables for a range of data-mining analyses using Monte Carlo simulations written in C++. Engineered features that improve search sensitivity for new particles, thereby reducing the necessary time and cost of experimental data collection for discoveries.Contributed to the writing of bids for research grants: National Science Foundation (NSF) Elementary Particle Physics (EPP) core grant ($1,033,000 US) and NSF Major Research Instrumentation (MRI) grant ($620,000 US).

Developed an algorithm in C++ and Python for real-time particle identification in streaming data that has an input rate of 1 GB/s. Optimised algorithm parameters and achieved excellent performance. This algorithm underpins a large part of the ATLAS experiment's physics programme by supplying data for numerous analyses. It has been used in production for data-taking since 2010 and has processed tens of petabytes of data, supporting the analysis work of approximately 3000 physicists.

Provided technical and administrative support to a range of key activities relating to the maintenance and dissemination of the UK's national time scale.