We’re looking for a talented Data Scientist to join our team for developing new disruptive products using the latest innovations in reinforcement learning, computer vision, and simulation. Data Scientist responsibilities include both sides of the data science and research engineer role. You will help our team train and deploy ML models from one side and do deep research from another side. You should have a strong problem-solving ability and a knack for statistical analysis.
Essential position responsibilities:
- Explore and implement challenging state-of-the-art algorithms;
- Train ML models for different tasks;
- Ensure Analytics model quality assurance and validate them;
- Implement swiftly demo quality prototypes;
- Convert proven useful prototypes into well-documented production-ready code;
- Optimize python code base for production models.
- At least 3+ years of experience researching and developing Machine Learning algorithms;
- Practical experience in developing Reinforcement Learning, CV solutions for game dev;
- Practical experience in developing Tabular Data & Time-Series solutions;
- Deep understanding of Machine Learning & Deep Learning concepts and algorithms;
- Experience with libraries and frameworks (PyTorch, OpenAI Gym, Scikit-learn, XGBoost, TensorFlow, etc.);
- Deep knowledge of statistics and linear algebra;
- Engineering background and great experience in Python;
- Ability to quickly prototype and implement new ideas, finding simple and accurate problem solutions;
- Ability to process and analyze huge data volumes, ability to create and check hypothesis including data visualization;
- Analytical thinking and exploratory state of mind. Strong research skills;
- Empathy and good communication abilities;
- Degree in Computer Science, Data Science, Mathematics or similar field.
Would be a big plus:
- Understanding of Unity basics;
- Docker, Kubernetes;
- Experience with deployment to the cloud;
- Experience developing and optimizing real-time software for high-loaded systems;
- Experience with large-scale machine learning (100GB+ datasets).