Part-Time Data Science Trainer (Remote)
Job Description Learning Saint is hiring an experienced Part-Time Data Science Trainer to deliver live, instructor-led online training to learners from technical and non-technical backgrounds. This role is ideal for professionals with strong hands-on Data Science experience who are comfortable teaching applied concepts in a structured, academic environment. Key Responsibilities • Deliver live online training sessions in Data Science and related technologies • Teach core concepts using practical, real-world examples and datasets • Guide learners through hands-on exercises, projects, and assignments • Conduct doubt-clearing and revision sessions • Support learners with capstone projects and applied problem-solving • Maintain course quality, curriculum standards, and session discipline • Collaborate with the academic team for assessments and learner progress Required Skills & Qualifications • Strong hands-on experience in Python and SQL • Solid understanding of Statistics, Probability, and Linear Algebra • Experience with Data Analysis, Data Visualization, and Exploratory Data Analysis (EDA) • Working knowledge of Machine Learning algorithms (Supervised & Unsupervised) • Experience using libraries such as Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn • Ability to explain technical concepts clearly to diverse learners • Prior teaching, mentoring, or corporate training experience preferred Preferred Qualifications • Experience working on real-world Data Science or Analytics projects • Exposure to tools such as Power BI, Tableau, or Excel (advanced) • Experience with Git/GitHub and project-based learning • Industry or academic certifications in Data Science or Analytics (optional) Who Should Apply • Working professionals with industry Data Science experience • Trainers, instructors, or mentors with live teaching exposure • Candidates comfortable conducting live online sessions • Individuals committed to learner success and academic quality Work Details • Mode: Remote (Online) • Type: Part-Time / Contract • Schedule: Flexible (as per assigned batches) Application Process Interested candidates may apply by submitting their resume. • Shortlisted candidates will be contacted for an interview and demo session. Apply tot his job