Job Details

We're looking for a Data Scientist to join a high-impact team focused on turning advanced machine learning and AI models into reliable, scalable production systems. This role begins with a strong emphasis on the engineering and operationalization of predictive models-ensuring they perform consistently in real-world environments.

Responsibilities:

• Deploy predictive and machine learning models into production environments.
• Build and maintain automated retraining pipelines and refit workflows.
• Develop and monitor model performance dashboards, alerts, and drift detection systems.
• Collaborate with data scientists, engineers, and business stakeholders to translate research into scalable solutions.
• Help define and implement best practices for MLOps, CI/CD, monitoring, and governance.
• Explore and integrate new tools within the MLOps ecosystem to improve reliability and scalability.
• Over time, expand into feature engineering, NLP, deep learning, and AI research initiatives.

• Master's degree in Computer Science, Applied Mathematics, Engineering, or a related quantitative field.
• Strong programming skills in Python or R; proficiency with SQL is a plus.
• Familiarity with cloud platforms such as Microsoft Azure, AWS, or GCP.
• Solid understanding of machine learning algorithms, statistics, and data modeling.
• Excellent problem-solving, collaboration, and communication skills.
• Experience with model deployment frameworks, workflow orchestration, or monitoring tools is highly desirable.