Part-Time Data Science Trainer (Remote)

🌍 Remote, USA πŸš€ Full-time πŸ• Posted Recently

Job Description

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

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