Trainer Data Science & Analytics - Bhopal

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Job Summary:

Data Science and Analytics Trainer

Key Responsibilities:

• Design and deliver engaging training sessions on:
• Python/R for data science
• Data wrangling and visualisation (Pandas, Matplotlib, Seaborn, Power BI, Tableau)
• Statistical analysis
• Machine learning (Supervised, Unsupervised, NLP)
• SQL and data querying
• Business analytics and decision-making using data
• Mentor learners on hands-on projects, capstone assignments, and case studies.
• Evaluate learners' progress through quizzes, assignments, and mock interviews.
• Assist in curriculum design and update training materials to align with industry standards.
• Conduct doubt-clearing sessions and one-on-one support.
• Collaborate with other trainers and program managers to improve learning outcomes.
• Stay updated with the latest tools, trends, and technologies in data science and analytics.

Required Skills and Qualifications:

• Bachelor’s/Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
• Strong knowledge of Python, R, SQL, Excel, and data visualisation tools.
• Hands-on experience with machine learning libraries such as Scikit-learn, TensorFlow, or Keras.
• Solid understanding of statistics, probability, and analytical problem-solving.
• Prior experience in teaching/training/coaching (preferred).
• Excellent communication and presentation skills.
• Ability to explain complex technical concepts simply and engagingly.

Good to Have:

• Industry certifications like Google Data Analytics, Microsoft Data Scientist Associate, or similar.
• Experience with Big Data tools (Spark, Hadoop) or Cloud platforms (AWS, GCP, Azure).
• Knowledge of BI tools like Tableau, Power BI.
• Familiarity with project lifecycle, model deployment, and version control (Git).

Why Join Us:

• Opportunity to shape future data scientists and analysts.
• Collaborative and growth-oriented work environment.
• Continuous learning and development opportunities.
• Flexible work arrangements and competitive remuneration.