Position: Data Scientist (Security)
Company: Scalarr
Category: Data Science
Experience required: 5y
English level: pre

If you feel passionate about making the world of networks and edge computing safer, join our team and get the chance to work with the latest innovations and technologies in the field. You’ll be employing the smartest SOTA approaches in DS/ML/RL to detect and prevent threats and strengthen cybersecurity. For security-driven tasks and challenges that will keep you engaged and motivated, read the description below.

**Responsibilities**
- Explore, train, and implement challenging state-of-the-art ML/RL algorithms to detect cybersecurity threats and anomalies in real-time. 
- Test and provide an analytics-based model for Quality Assurance. 
- Implementation of SOTA approaches
- Prototype quickly and implement new ideas with the help of ML and RL. 
- Convert proven, useful prototypes into well-documented and production-ready code.
- Optimize Python codebase for production models.


**Requirements**
- At least 5+ years of experience in Machine Learning algorithms research and development.
- Proven practical experience in building and training Unsupervised, Semi-Supervised, and Data Clustering models.
- Practical experience in developing Tabular Data & Time Series models.
- Deep knowledge of statistics and linear algebra.
- Engineering background as you’ll be actively using Python.
- Ability to quickly prototype and implement new ideas, finding simple and accurate problem solutions with the help of ML and RL algorithms.

**Would be a big plus**
- Practical experience in developing ML algorithms for detecting anomalies and cybersecurity threats.
- Practical knowledge and understanding of Reinforcement Learning in cybersecurity.
- Rust, C++.
- Experience in developing solutions for IoT & Edge and network security.

**We offer**
- Professional development in semi-supervised, self-supervised models, anomaly detection, reinforcement learning and Security Patterns Detection and Prevention. 
- Participation in the full cycle of product development, having a real opportunity to improve it.
- No legacy code.
- Professional growth in a multicultural and international team.
- Competitive salary and comprehensive benefits package.