Position: Data Scientist
Category: Data Science
English level: fluent
Years of experience: 1


I have participated in two data science projects so far. One is on-going cooperation with gainkit.com and another was freelance job on the Upwork.

About Gainkit:
Website suffers from users which find fraud ways to abuse and siphon
money out of it. Using website's database, I created stacked model (with
tree-based models inside) which identifies such users with ¬92%
(tested with cross-validation). Deployed model as API using Heroku
(PaaS). Currently me and website owner are testing model on new
users and working on further variables engineering to boost model's
performance.
Libraries used: numpy, pandas, matplotlib, seaborn, ipinfo, datetime, scipy, sklearn, lighgbm, xgboost

Upwork job:
First task was to optimize hyperparameters for four different
models so when they are trained on new datasets they would show
best performance on average. Second task was to perform feature
selection pipeline with criterion developed for customer. In addition,
created manual which explains how to add new model to the pipeline
Libraries used: os, ast, datetime, pandas, numpy, matplotlib, seaborn, sklearn, lightgbm, xgboost


I have also about 5 years of experience in investment banking. Mostly I worked in the back office as a reconciliation specialist in UBS and BNY Mellon, reconciling clients' accounts, positions, various instruments trades and cash flows.
In Credit Suisse, where I currently work, I am working in the trade management helping London traders to facilitate their business. Mostly that business is in interest rate instruments (especially swaps). My responsibilities are mainly related to trades margin optimization, portfolio compression - i.e. decrease number of trades in traders portfolios with cooperation with intermediary and other banks to decrease bank's liabilities. Also I have worked on few automations using python.