Data Science Specialist

Experience:

Must have skills required : Machine Learning, NLP OR Computer Vision OR Statistics OR pandas OR NumPy, Python

Role & responsibilities

• Teach Applied AI/ML:

  Design and deliver practical, project-based courses in AI/ML(

  Python for ML, Statistics, ML Algorithms, Deep Learning, NLP, CV, ML Ops, GenAI

  ).

• Develop Industry-Relevant Curriculum:

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

• Mentor Student Projects:

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

• Guide & Mentor Students:

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

• Stay Current:

  Bring the latest AI/ML research, tools, and industry trends into the classroom.

• Collaborate:

  Work closely with other expert faculty and staff to create a unified and effective learning experience.

• Assess Practical Skills:

  Design and evaluate assignments, projects, and assessments focused on real-world applications.

Qualifications and Requirements:

• Bachelors or Masters degree in Computer Science, Engineering, Data Science, AI/ML, or related field. (PhD is valued but not mandatory.)

• 7+

  years of direct, hands-on professional experience in the tech industry as an AI/ML Engineer, Data Scientist, Research Scientist, or similar role involving AI/ML development and deployment.

• Proven Industry Track Record:

  Demonstrated experience in building, training, and deploying machine learning models (including deep learning) for real-world problems.

• Deep AI/ML Understanding:

  Strong grasp of core

  ML algorithms (classical & deep learning CNNs, RNNs, Transformers)

  , model evaluation, statistics, and awareness of current research/industry trends.

• Passion for Teaching/Mentoring:

  Ability to explain complex concepts clearly and guide others. Prior mentoring, corporate training, technical workshops, or project supervision experience is highly relevant.

Required Skills:

• Technical:

  Expert-level Python programming.

• Proficiency with data science libraries

  (Pandas, NumPy, Scikit-learn).

• Hands-on experience with ML/DL frameworks

  (TensorFlow, PyTorch

  ).
• Strong

  SQL

  and

  data handling skills

  .
• Understanding of

  ML Ops

  practices and tools (

  Git, Docker, AWS/GCP/Azure

  ).
• Knowledge of key AI areas (

  NLP, Computer Vision, Generative AI/LLMs

  ).
• Soft Skills: Strong communication, mentoring ability, collaboration, and a genuine passion for education.