Data Scientist + Associate Instructor

Key Responsibilities:

• Teach Applied AI/ML:

  Design and deliver practical, project-based courses in AI/ML, including Python for ML, Statistics, ML Algorithms, Deep Learning, NLP, Computer Vision, ML Ops, and Generative AI.

• Develop Industry-Relevant Curriculum:

  Design and update the AI/ML curriculum to reflect current industry tools, techniques, and best practices, incorporating professional experience and case studies.

• Mentor Student Projects:

  Guide students through hands-on AI/ML projects, providing technical direction, code reviews, and feedback.

• Guide & Mentor Students:

  Advise students on practical skills, career paths in AI/ML, and preparation for internships and job placements.

• Stay Current:

  Maintain expertise in the latest AI/ML trends and technologies, integrating knowledge into teaching.

• Collaborate:

  Work with industry-expert faculty and staff to create a unified learning experience.

• Assess Practical Skills:

  Create and evaluate assignments, projects, and assessments focused on practical application and understanding.

Required Qualifications & Experience:

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, AI/ML, or similar field.
• 1-5 years of hands-on professional experience as an AI/ML Engineer, Data Scientist, Research Scientist, or similar role.
• Proven experience building, training, and deploying machine learning models, including deep learning.
• Strong grasp of core ML algorithms (classical and deep learning, CNNs, RNNs, Transformers), model evaluation, statistics, and industry trends.
• Passion for teaching and mentoring, including experience in corporate training, workshops, project supervision, or technical content creation.

Required Skills:

• Expert-level Python programming
• Data science libraries: Pandas, NumPy, Scikit-learn
• ML/DL frameworks: TensorFlow, PyTorch
• SQL and data handling skills
• ML Ops practices and tools: Git, Docker, Cloud platforms (AWS, GCP, Azure)
• AI areas: NLP, Computer Vision, Generative AI/LLMs

Good-to-Have:

• Prior undergraduate or graduate teaching experience
• Familiarity with modern teaching methodologies and academic tools