Master’s degree in Computer Science, Engineering, or a related technical field wih a miniumum 3 years' experience and at least 2 years' in Data Science.
Strong programming skills in Python, SQL, PySpark and proficiency in data science libraries (e.g., scikit-learn, pandas, NumPy).
Mastery of machine learning fundamentals and statistical modelling.
Knowledge of LLMs and Azure AI stack / services including Azure AI Foundry and Copilot Studio.
Strong problem-solving skills and a passion for learning new technologies.
Demonstrated ability to leverage AI tools (e.g., GitHub Copilot, Azure AI Foundry) for code generation, automation, and productivity enhancement.
Ability to work collaboratively in a team environment and communicate technical concepts clearly.
Demonstrated ability to drive innovation and deliver results in a fast-paced environment.
Preferred Qualifications
Proficiency in multiple programming languages and development frameworks.
Familiarity with DevOps practices, CI/CD pipelines, and Infrastructure as Code.
Familiarity with version control systems (e.g., Git).
Experience with Generative AI and familiarity with Microsoft’s AI ecosystem and tools such as Copilot Studio.
Knowledge of security, compliance, and Responsible AI principles in software development.
Experience with Azure cloud platform and building distributed systems or web services.
Responsibilities
Design, develop, and deploy robust AI/ML models that support business objectives.
Conduct exploratory data analysis and communicate findings to stakeholders.
Collaborate with cross-functional teams—including product managers, data scientists, data engineers and UX designers—to deliver end-to-end features from concept to production.
Participate in code reviews, architecture discussions, and contribute to data science and engineering best practices.
Assist in building and maintaining models and data science pipelines for MCAPS business units.
Write well-documented, high-quality, and maintainable code.
Ensure solutions adhere to Microsoft’s Responsible AI principles, compliance, and security standards.
Contribute to a culture of inclusion, innovation, and technical excellence within the AIT organization.