Data Analyst and Machine Learning Engineer:

* Data analysis, cleaning and structuring (Python:Pandas).* Data visualization (Python: Seaborn, Matplotlib).

* Anomaly detection and removal (Decision Trees).

* Data preprocessing (Python, Scikit-learn, Keras,TensorFlow ).

* Machine learning for detecting fraud transactions using boosting models - XGBoost, LightGBM and neural networks based on Keras and TensorFlow software library.

* Hyperparameters optimization of ML-models.

* Final analysis of results and identifying the best ML-models.

* Deployment of ML-models in a production environment (Django, Docker).

Oct 2022 - Present - Integration Manager:

* Client communication and explanation of existing system capabilities (Jira).

* Receiving test or production access credentials from clients for service providers planned for integration (Jira).

* Documenting the integration process (Trello).

* Creating client requirements-based "User Stories"(GitLab-Wiki).

* Developing or testing (if available) integration packages for test API transactions based on Postman collections (Postman, Curl).

* Reviewing existing documentation.

* Creating digital self-signed certificates and sending them to support of service providers for signing (Linux).

* Coding required hash functions for signature encryption using various algorithms (MD5, SHA-256) across multiple programming languages (Java, PHP,Javascript, Perl, Python).

* Creating API requests (REST JSON/XML, Host-to-Host) as described in "User Stories".

* Problem-solving: direct communication with service provider technical support in case of integration issues in multiple languages including English(Telegram , Email, Jira).

* Setting up client back offices at different companies banks and payment systems.

* Use Cases: technical description of the integration process (Confluence, GitLab-Wiki).

* Dev Support: assisting developers in understanding integration nuances for faster implementation of client requirements (Slack).