Curriculum vitae

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Education

McGill University, Montréal

• M.A. Political Science (Thesis), comparative politics.
• Supervisor: Prof. Aaron Erlich.

Jesus College, University of Oxford

• B.A. (Hons) Philosophy, Politics, and Economics.
• Undergraduate thesis in Politics, awarded 82, ranked 1^st in cohort: ‘Neural topic modelling of Russian strategic frames during Moldova’s 2024 elections.’

St Paul’s School, London

• A-level Mathematics, Economics, Politics (all A*); 12 A* GCSEs.

Research

Strategic frames in Moldova’s 2024 elections

• To my knowledge, the first cross-corpus computational frame analysis of Moldova’s 2024 electoral cycle: 321,241 messages from 53 mostly pro-Russian Telegram channels, paired with 15,176 alignment-coded press articles.
• Built the pipeline end-to-end: fine-tuned Russian sentence transformer, BERTopic topic discovery, XGBoost frame classification; validated against independently published coding schemes.
• Pro-Kremlin messaging resolves into four frames plus an off-theme residual: domestic elite contestation (42.7 per cent) outweighs the imperial-identity register the literature centres on.

Do algorithms amplify identity?

• Recommender-system audits across Moldova, Ukraine, Latvia, and Georgia: whether platform amplification systematically favours identity-based content, and whether that varies by country.

Professional experience

Banque Banorient France, London

Banking operations intern

• Cross-departmental rotation through treasury and money markets, credit risk, compliance, and front and back office.
• Certified in AML/KYC, sanctions screening, conduct risk, and data protection; documented interdepartmental workflows and flagged manual data-handling failures.

2XL Capital Partners Ltd

Equity research analyst (part-time)

• Independent company and sector research for a private asset-management office; findings delivered as written theses and briefings to the CIO.
• Built quantitative valuation models across technology and data-infrastructure sectors.

Teaching

• Volunteer A-level and GCSE tutoring in Mathematics and Economics, 2022–present.

Skills

• Programming: Python, R, SQL, JavaScript, Bash/zsh.
• Methods: neural topic modelling, transformer fine-tuning, supervised classification, mixed-effects models, time-series analysis, discourse analysis, mixed methods.
• Data engineering: web scraping and archiving, reproducible pipelines, corpus construction at scale.
• Tools: sentence-transformers, BERTopic, XGBoost, git, ffmpeg, Whisper, LaTeX and Typst.
• Languages: Russian (native), English (native), French (working).

Additional information