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Experience &
education.

Certified AI Ethicist and Data Scientist with about 5 years of UK public sector experience, following 6.5 years in semiconductor engineering at Samsung Electronics. Specialised in large-scale analytics, AI engineering, and healthcare workforce modeling. Proven track record of building LLM-powered applications in Python and PySpark, while leading reproducible, secure analytics engineering for the NHS workforce across England.

Python PySpark Databricks Azure (ADLS Gen2) SQL R Machine Learning LLMs & RAG AI Engineering Tableau Git Agile / Jira

Experience

  • Apr 2024 — Present

    Data Scientist

    NHS England · London, UK

    • Redesigned the CT1 training-place allocation methodology from a weighted multi-criteria model into a rule-based model in Python and Excel, presenting outputs via Tableau to inform prioritisation for under-doctored deaneries during 2024 BMA industrial-action negotiations.
    • Lead Developer for the 10-Year Workforce Plan modelling under NHS England's Business Critical Model (BCM) governance: validating the model's key assumptions in Python and PySpark, working with Department of Health and Social Care and NHS England policy leads to shape the response to National Audit Office recommendations, and presenting model components to the External Scrutiny Panel.
    • Manage the project's dedicated Azure Data Lake Storage (ADLS Gen2) and Databricks clusters, coordinating with UDAL Data Engineers on secure environments; co-led the migration of legacy PySpark pipelines off deprecated DBFS onto Entra-secured Data Lake containers, and coordinated Windows 11 migration testing to protect BCM continuity.
    • Led the transition of legacy Excel workforce models into automated Databricks and Python pipelines with documented assumptions, strengthened data lineage and peer-reviewed Git version control; refactored the Python codebase to cut model runtime by around half and enable cross-functional teams to extend it.
    • As Community Pharmacy modelling workstream lead, coordinated a dozen stakeholder groups — including pharmacy Deans and Chief Pharmaceutical Officers — into a single delivery scope, launched a Pythonised supply-and-demand model within six months, secured the model SRO's approval despite late changes to baseline and counterfactual assumptions, and presented it at the national consultation on Community Pharmacy workforce interventions.
    • Designed an NLTK-based sentiment-analysis pipeline for the Reporting, Insights, Publications and Transparency programme and contributed to a paper on insights maturity for the CEO's office and Board; applied NLP and sentiment analysis to meeting transcripts to assess staff views on organisational change and internal AI adoption.
    • Conduct horizon scanning of emerging data and AI engineering practice, including exploratory research into AI-enabled gains in workforce productivity.
    • Delivered Python, Databricks, PySpark and Git training and onboarding for analysts and new data scientists, promoting coding best practice across the modelling team.
  • Jun 2022 — Mar 2024

    Junior Data Scientist

    Health Education England · London, UK

    • Maintained a pythonised geo-spatial analysis and produced Tableau dashboards analysing clinical placement capacity, workforce supply trends and geographic demand across 65 medical specialties for the HEE Board's tariff-funding review, advising medical Deans on redistributing specialty training posts and informing NHSE's recommendations to the Office for Students on new dental school places.
    • Supported R modelling to predict complex birth deliveries for maternity service planning, using source data from RCOG statisticians.
    • Collaborated with Data Engineering and Product teams on Jira / Agile to manage project timelines.
  • Apr 2022 — Jun 2022

    Data Manager

    UCL Great Ormond Street Institute of Child Health · London, UK

    • Worked with bioinformaticians and statisticians on the GSK Sotrovimab Covid-19 study, cleaning and transforming lab data.
    • Designed a MySQL server for secure data transfers from study entry points.
  • Jul 2011 — Jan 2018

    Engineer

    Samsung Electronics, Foundry Business · Gyeonggi-do, South Korea

    • Operated Chemical Vapour Deposition (CVD) equipment in 24/7 shift operations for high-volume 32/28nm and 14/10nm semiconductor production, and supported set-up and ramp-up of a new 7/10nm line.
    • Established maintenance SOPs and data-driven part-replacement criteria by evaluating correlations between plasma process parameters and component condition.
    • Derived optimal process conditions through simulation built on deposition and clean measurements, suppressing particle generation and improving yield.
    • Owned equipment asset and standards management on the Equipment Engineering System (EES): built gas and chemical usage metering and monitoring that detected unnecessary utility consumption and cut costs; with EES Master privileges, configured thin-film unit-process alarms and implemented Tool-to-Tool Matching (TTTM).

Selected Projects

  • Strategic Planning

    10-Year Workforce Plan modelling

    NHS England · DHSC

    • Refreshing the NHS Long-Term Workforce Plan modelling (published Jun 2022) with a multidisciplinary group, incorporating National Audit Office feedback.
  • AI & ML

    LLM & machine learning prototypes

    NHS · Hackathons & conferences

    • Endo Loop — non-diagnostic, at-home pattern journal for endometriosis and chronic pelvic pain, combining voice or manual symptom logs with wearable signals in a deterministic pattern engine with safety rules and a clinician-ready summary; 4th place at the eMed & OpenAI Reimagine Health hackathon (Jul 2026).
    • NoteGuard — trust layer for clinical AI: a LangGraph agent (Gemini + Tavily) that de-identifies NHS clinical free-text before any model sees it, so an LLM can safely draft discharge summaries, with a measured residual-PII trust score; built at the {Tech: Europe} London AI Hackathon (Jun 2026) and deployed on Hugging Face Spaces.
    • NHS Policy Navigator — adaptive Retrieval-Augmented Generation pipeline over the published 10-Year Health Plan and public NHS news feeds, built at the MongoDB Agentic Evolution Hackathon (May 2026) and refined with a working group through a spec-driven development cycle at near-zero infrastructure cost.
    • Pharmacy First agent — LLM-powered analysis of NHS pharmacy operations, open-sourced and presented at PyConUK, NHS RPySOC and HACA 2025.
    • Reducing missed NHS appointments — ML solution for a No. 10 Downing Street data science hackathon (Sep 2025), targeting waitlist cost.
    • NHS Career Coach — multilingual career-guidance chatbot on Azure AI Foundry that retrieves and cites Health Education England careers content and adapts its guidance to user personas; 2nd place at the NHS England, Microsoft & Kainos Hack for Health hackathon (Nov 2024; NHSE Data Science & Applied AI team blog).
    • OPEL prediction — ML models on the NHS Federated Data Platform during a Palantir & KPMG hackathon (Nov 2024).
  • Teaching & Outreach

    AI Engineering training programme

    Undergraduates to NHS analysts & clinicians

    • Designed and delivered a training programme teaching reproducible software engineering, responsible AI and governance principles using open-source NHS datasets and public repositories; accepted as a peer-reviewed oral presentation in computer science education.
  • Research

    Publications

    Peer-reviewed paper · Textbook

    • Kim, C. and Jiménez-Ruiz, E. (2022) CitySAT: a System for the Semantic Answer Type Prediction Task. CEUR Workshop Proceedings, Vol. 3119 (SMART 2021, ISWC Semantic Web Challenge), pp. 77–88. First author.
    • Foundations of Programming, Statistics, and ML for Business Analytics — developed R and Python conversion code for the English edition (Apr 2023); co-authored the Korean translated edition (Feb 2025).

Education

  • 2020 — 2021

    MSc Data Science — Distinction

    City St George's, University of London

    • Ranked 1st on the global leaderboard of the International Semantic Web Conference (ISWC) 2021 SMART Challenge as a sole entrant with CitySAT, a two-stage hybrid system using Logistic Regression for answer category and literal types and a Multi-Layer Perceptron over ~760 DBpedia ontology classes; achieved 98.4% accuracy and 84.2% NDCG@5 on the official test set, and delivered an oral presentation and a poster at ISWC in October 2021.
  • 2018 — 2020

    PGCert. Data Analytics

    University of Sheffield

    • Modules: Computer Security and Forensics, Machine Learning and Adaptive Intelligence, Statistical Data Science in R.
  • 2007 — 2011

    BSc Electronic Engineering

    Kyungpook National University · Daegu, South Korea

    • Modules: Electronic Engineering Lab (MATLAB), Calculus, Numerical Analysis.

Certifications

Community & Volunteering

  • 2025 — 2026

    Global Ambassador

    LangChain · London

    • Hosted technical meetups and organised a hackathon in central London.
    • Collaborated with AI builder communities across North and South America (including Halifax and Buenos Aires) in 2025, and with engineering communities across Europe (including Amsterdam, Munich, Zurich, Stockholm and Paris) in 2026.
  • 2026

    UK–Korea Global Health Forum working group

    London School of Hygiene & Tropical Medicine

    • Organised a conference with senior researchers at LSHTM.
  • 2026

    Professional Mentor

    University of Greenwich · City St George's

  • 2026

    Conference & community organiser

    PyCon UK · London tech meetups

    • Volunteered at PyCon UK and other leading UK technology conferences; planned or helped run local meetups ranging from 50 to 600+ attendees.