Note: The job is a remote job and is open to candidates in USA. Scalarr is seeking a Senior Data Scientist to develop machine learning and reinforcement learning solutions for real-time cybersecurity threat and anomaly detection. The role involves researching, prototyping, testing, optimizing, and productionizing ML/RL models and Python code.
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 code base for production models
Skills
- 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
- Practical experience in developing ML algorithms for detecting anomalies and cybersecurity threats
- Practical knowledge and understanding of Reinforcement Learning in cybersecurity
- Experience in developing solutions IoT & Edge and network security
- Rust, C++
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