I'm a data analyst and ML engineer who treats analysis as the last mile before a decision. Across seven self-directed projects I've worked end to end — quantitative risk modelling, NLP, fraud detection, data governance, MLOps monitoring, and a full-stack finance app — and written each one up the way I'd present to a stakeholder: the finding first, the methodology second.
What pulls me into this work is the point where a model becomes a recommendation — the threshold that turns into dollars a day, the drift signal that buys two weeks of warning, the VaR number that changes how a portfolio is weighted. I care as much about communicating that clearly as about getting it right.
[Add a couple of sentences here about your background — where you studied, how you got into data, and what you're like to work with. This is the one part of the site only you can write.]
I'm looking for a [data analyst / ML engineer] role where rigorous analysis drives real decisions — ideally in [your target domains, e.g. finance, risk, or ML platforms]. If that sounds like your team, let's talk.