Design, develop, and apply optimization algorithms to improve system performance, model efficiency, and data processing pipelines.
Work on data science and machine learning projects using Python frameworks such as Pandas, NumPy, SciPy, Scikit- learn, and Keras.
Contribute to the design of scalable, secure, and efficient software systems.
Stay up to date with emerging trends and best practices in Python, data science, MLOps, cloud computing, and optimization techniques.
Ensure data security, privacy, and compliance with relevant data protection standards.
Experience or solid understanding of MLOps concepts, such as model lifecycle management, deployment, and monitoring.
Understanding of ORM libraries and database integration.
Hands- on experience with Microsoft Azure or other cloud platforms (Azure preferred).
Implement and maintain MLOps pipelines, including model versioning, monitoring, retraining, and CI/CD for ML workflows.
Practical experience with data science and machine learning frameworks (Pandas, NumPy, Scikit- learn, etc.).
Familiarity with version control systems such as Git.
Write clean, maintainable, and well- documented code; perform unit testing and code reviews.
At least 2 years of experience working as a Data Scientist, Machine Learning Engineer, or similar role.
Bachelor’s degree in Computer Science, Engineering, or a related field.
Knowledge of Python’s threading limitations, multiprocessing, and event- driven programming.
Fluent in written and spoken English.
Build, train, evaluate, and optimize machine learning models for production use.
Collaborate with cross- functional teams to design, develop, and implement data- driven features and solutions.
Strong proficiency in Python programming.
Ability to integrate and process data from multiple sources and databases.
Deploy and manage data science and machine learning solutions on Microsoft Azure (e.g., Azure ML, Azure Storage, Azure Compute).
Preferred Qualifications
Experience deploying machine learning models in production environments.
Hands- on experience with Azure Machine Learning, Docker, or CI/CD pipelines.
Strong understanding of optimization algorithms and their application in data science or software systems.
Experience working in data- intensive or ML- driven products.
Familiarity with Django or backend frameworks is a plus.
