Security engineer and data analyst. I don't stop at "it works" — I measure everything until it tells me something I didn't expect, then write down the result that contradicts the obvious assumption.
I spent three years as a product analyst in India — SQL, Python, dashboards, and forecasting — before moving to Germany. I'm now finishing an MSc in Cyber Security in Berlin, with a dissertation building an ML-based intrusion detection system on AWS.
That path put me on the bridge between data and security, which is exactly where I want to work. My recent 30-day challenge — ten projects across both tracks, each shipping a measured finding rather than just working code — is how I keep sharpening that combination.
What I care about: distrusting results that flatter the design, profiling before optimising, and being able to name exactly where a guarantee ends. I'm looking for a working-student or analyst role where I can work across data and security.
The tools and concepts I reached for across the projects — edit freely to match how you'd describe yourself.
Ten projects, one discipline: build the core, do the hard half, then break it and measure. Filter by track.
Current research and peer-reviewed work.
Designing and evaluating a machine-learning intrusion detection system deployed on AWS — building the detection models, the cloud pipeline that feeds them, and an honest evaluation of where they hold up and where they don't. Repo ↗
Co-authored IEEE conference paper on bringing a conventional oven into the connected era — replacing manual knobs with automated, remotely controllable operation. DOI ↗
Open to conversations about security engineering and data roles — or just to swap notes on any of the projects above.