Web3 Talent

I’m a hybrid analyst who bridges the gap between data science and commercial strategy. My work sits at the intersection of quantitative finance, machine learning, and business development, translating messy datasets into insights that drive real-world commercial outcomes.

What I bring to the table:

Financial Analytics & Modelling: Skilled in DCF, bottom-up financial modelling, and market analysis. My Master’s thesis quantified how geopolitical uncertainty reshapes IPO markets, proving that high risk reduces VC-backed IPO volume by 10.5% through compositional selection rather than direct pricing.

Data Science Toolkit: Python (pandas, NumPy, scikit-learn), SQL (MySQL), and supervised/unsupervised ML. I’ve processed retail transaction data, standardised product names via fuzzy matching and LLM integration, and executed A/B testing with T-tests.

Commercial Instinct: Co-founded an education startup and secured public-sector grants; previously exceeded MQL-to-SQL conversion rates by ~50% in B2B tech sales. I don’t just analyse data; I understand the commercial logic behind it.

Currently completing my MSc at the University of Jyväskylä (graduation May-June 2026), with international exchange studies in finance and information management at National Yang Ming Chiao Tung University. I am currently working independently as a Data Analyst at Start Consulting, where I architect Python-based data pipelines and advise early-stage founders on go-to-market strategy.

Open to analyst, quantitative finance, and data-centric strategy roles in Helsinki, London, or remotely. Let’s connect if you’re working at the crossroads of data, finance, and commercial decision-making.