Education and Experience Required:



Bachelor's or master's degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline.



Typically, - years' experience.







Knowledge and Skills:



Deep understanding of machine learning algorithms, such as linear regression, decision trees, support vector machines, random forests, deep learning models (, neural networks), and reinforcement learning. Proficient in model selection, hyperparameter tuning, and evaluating model performance using appropriate metrics.



A strong foundation in mathematics and statistics. In-depth knowledge of linear algebra, calculus, probability theory, and statistical concepts. Understanding and developing complex machine learning models and algorithms.



Proficiency in programming languages such as Python, R, or Java is expected. Ex...