Data Science & Machine Learning - Working Professional

As a Learning Data Science/Machine Learning Professional at our organization, you will be responsible for conducting live instruction sessions to teach core topics in data science and machine learning. These topics include supervised and unsupervised learning, deep learning, model evaluation, and MLOps. You will engage with learners through interactive sessions to ensure a comprehensive understanding of the subject matter. Collaboration with content teams is a crucial aspect of this role. You will work closely with these teams to design labs, conduct code walkthroughs, and develop real-world case studies utilizing Python, scikit-learn, TensorFlow/PyTorch, and cloud-based data science and machine learning services. Your input will contribute to the creation of a dynamic and engaging curriculum. In addition to live instruction and curriculum collaboration, you will provide support to learners by addressing technical queries, debugging code, reviewing notebooks, and offering constructive feedback on assignments and projects. Your mentorship will extend to guiding learners on capstone projects such as image/video models, NLP pipelines, recommendation systems, and deployment pipelines. Continuous improvement is a key focus area of this role. You will analyze learner performance data to refine modules, introduce emerging topics like transformers and generative models, and enhance assessments to ensure an enriching learning experience. To be successful in this position, you should possess a minimum of 3 years of industry or academic experience in data science, machine learning, or artificial intelligence. A Master's degree in Data Science, Machine Learning, AI, or a Computer Science specialization in AI and Data Science/Machine Learning is required. Proficiency in Python and ML frameworks such as scikit-learn, TensorFlow, or PyTorch is essential. Familiarity with MLOps tools like Docker, Kubernetes, MLflow, and cloud ML services such as AWS SageMaker, GCP AI Platform, or Azure ML is highly desirable. Strong presentation and mentoring skills in live and small-group settings are crucial for this role. Previous teaching or educational technology experience would be a significant advantage in fulfilling the responsibilities of this position.,