Data Scientist - IT

About the Role:

We are seeking a dynamic and experienced Data Scientist with expertise in MLOps to bridge the gap between industry practices and academic excellence. This role uniquely combines technical leadership with academic responsibilities, including curriculum design, classroom delivery, and mentoring students on real-world AI/ML applications.

You will play a key role in shaping the next generation of AI professionals by delivering hands-on, project-based learning experiences aligned with industry standards.

Key Responsibilities:

- Design and deliver project-based coursework in MLOps and Applied AI

- Conduct lectures, workshops, and lab sessions on machine learning and production-grade systems

- Develop curriculum covering end-to-end ML lifecycle, including model development, deployment, monitoring, and optimization

- Teach and implement real-world use cases using industry-relevant tools and frameworks

- Mentor and guide students on capstone projects, research work, and practical implementations

- Evaluate student performance through assignments, projects, and assessments

- Stay updated with the latest trends in AI, ML, and MLOps, and integrate them into course content

- Collaborate with internal teams to align curriculum with industry needs and product capabilities

- Contribute to thought leadership, content creation, and knowledge sharing initiatives

Required Candidate Profile:

- Strong experience as a Data Scientist, ML Engineer, or MLOps Practitioner

- Expert proficiency in Python programming

- Hands-on experience with machine learning frameworks such as TensorFlow and PyTorch

- Practical experience with MLOps tools like MLflow, Kubeflow, or Apache Airflow

- Deep understanding of the machine learning lifecycle, including deployment and monitoring

- Experience in designing and delivering technical training, workshops, or academic programs

- Strong communication and presentation skills with the ability to simplify complex concepts

- Passion for teaching, mentoring, and knowledge sharing

Preferred Qualifications:

- Experience in curriculum design or academic instruction in AI/ML domains

- Exposure to cloud-based ML platforms (AWS, Azure, GCP)

- Knowledge of data engineering and pipeline orchestration

- Familiarity with containerization and orchestration tools (Docker, Kubernetes)

- Advanced degree (Masters/PhD) in Computer Science, Data Science, AI, or related field