Open to Data Science roles
Kseniia Melnikova
Network Traffic Analyst Data Scientist
I came to data science from bank cybersecurity, where a model runs in production and its mistakes become real incidents. That taught me to value clean data, honest validation and results that hold up outside the notebook.
01whoami
Signal in the noise
02experience
Three years in bank cybersecurity
03education
University and further training
04skills
Tools I can put to work
No self-assigned percentages. Each item says where I used it and what the work involved.
05projects
Selected project
06interactive
The Anomaly Lab
This is a place to play with anomaly detection and see what a single score usually hides. The detector first learns what normal traffic looks like, then decides which new events seem suspicious. Move the threshold down and it catches more anomalies but raises more false alarms. Move it up and the screen gets quieter, while more attacks slip through. The simulation knows the correct answer for every event, so precision, recall and false-positive rate are real. Try choosing a threshold or fooling the detector.
Click the field: add a normal event · Shift+click: add an anomaly
Detector metrics
07off the clock
Life outside the notebook
Away from data, I travel to get under the skin of a place — its language, its habits, its food. I love river rafting, camping and hiking, and I photograph it all on my own camera. Before I moved, I was into postcrossing: trading handwritten postcards with strangers around the world.
08contact
Let’s talk
I’m interested in problems where training a model is only half the job. The other half is understanding the data, testing the result honestly and explaining what it means. If that sounds relevant to your team, or you just want to say hi, drop me a line.
Email or Telegram, whichever is easier.