Data Scientist Instructor (Teaching role)

Job Description

Key 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 curriculumto reflect current industry tools, techniques, and best practices, incorporating yourprofessional experience and case studies. Mentor Student Projects: Guide students through hands-on AI/ML projects, providingtechnical 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 theclassroom. Collaborate: Work closely with other expert faculty and staff to create a unified andeffective learning experience. Assess Practical Skills: Design and evaluate assignments, projects, and assessmentsfocused 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.) 5 years of direct, hands-on professional experience in the tech industry as anAI/ML Engineer, Data Scientist, Research Scientist, or similar role involving AI/MLdevelopment and deployment. Proven Industry Track Record: Demonstrated experience in building, training, anddeploying machine learning models (including deep learning) for real-world problems. Deep AI/ML Understanding: Strong grasp of core ML algorithms (classical & deeplearning CNNs, RNNs, Transformers), model evaluation, statistics, and awarenessof current research/industry trends. Passion for Teaching/Mentoring: Ability to explain complex concepts clearly andguide others. Prior mentoring, corporate training, technical workshops, or projectsupervision experience is highly relevant. (Formal academic teaching experience isnot mandatory.)Required Skills: 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 genuinepassion for education.Good-to-Have: Prior teaching experience at the undergraduate or graduate level. Familiarity with modern teaching methodologies and academic tools. Key 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 curriculumto reflect current industry tools, techniques, and best practices, incorporating yourprofessional experience and case studies. Mentor Student Projects: Guide students through hands-on AI/ML projects, providingtechnical 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 theclassroom. Collaborate: Work closely with other expert faculty and staff to create a unified andeffective learning experience. Assess Practical Skills: Design and evaluate assignments, projects, and assessmentsfocused 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.) 5 years of direct, hands-on professional experience in the tech industry as anAI/ML Engineer, Data Scientist, Research Scientist, or similar role involving AI/MLdevelopment and deployment. Proven Industry Track Record: Demonstrated experience in building, training, anddeploying machine learning models (including deep learning) for real-world problems. Deep AI/ML Understanding: Strong grasp of core ML algorithms (classical & deeplearning CNNs, RNNs, Transformers), model evaluation, statistics, and awarenessof current research/industry trends. Passion for Teaching/Mentoring: Ability to explain complex concepts clearly andguide others. Prior mentoring, corporate training, technical workshops, or projectsupervision experience is highly relevant. (Formal academic teaching experience isnot mandatory.)Required Skills: 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. Un

Keyskills :
data scienceNumPySQLPython programmingPandasScikitlearnMLDL frameworksTensorFlowPyTorch