• Advanced mathematical and statistical skills in subjects like linear algebra, calculus, and Bayesian statistics.
• Degree in computer science, mathematics, statistics, or a related field.
• Professional knowledge in machine learning, neural networks, deep learning, or related fields.
• Analytical, problem-solving, and team player.
• Software engineering skills.
• Knowledge in data science.
• Coding and programming languages: Python, Java, C++, C, R, and JavaScript.
• Understand ML frameworks, libraries and packages, data structures, data modeling, and software architecture.

Overall Responsibilities

• Designing ML systems.
• Design and create AI algorithms capable of learning and making predictions.
• Researching and implementing ML algorithms and tools.
• Identifying appropriate data sets, data representation methods, differences in data distribution, and verifying data quality.
• Transforming and converting data science prototypes.
• Performing statistical analysis.
• Running machine learning tests and using results to improve models.
• Training and retraining systems when needed.
• Extending machine learning libraries.
• Developing machine learning apps according to client requirements.