Python Trainer
Boston Institute of Analytics - Nandyal Checkpost, Kurnool
Location
🇮🇳 Kurnool, India
Type
full_time
Salary
Undisclosed
Posted
2w ago
Job Description
Company Description Boston Institute of Analytics (BIA) is an international training organization focused on developing job-ready professionals in analytics, data science, and related technology fields. The Nandyal Checkpost, Kurnool center offers industry-oriented programs designed to equip learners with practical, in-demand skills. BIA collaborates with experienced trainers and industry partners to align its curriculum with current market needs. The institute emphasizes hands-on learning, career readiness, and professional development for students and working professionals. Joining BIA as a trainer provides the opportunity to shape future talent and contribute to the growth of the analytics and technology ecosystem in the region. Role Description The Python Trainer will deliver classroom-based instruction in Python programming at the Nandyal Checkpost, Kurnool campus in a Part-time, on-site capacity. Day-to-day
responsibilities
include planning lessons, preparing teaching materials, and conducting interactive sessions that cover core Python concepts, libraries, and best practices. The trainer will guide learners through hands-on coding exercises, projects, and assessments, providing constructive feedback and mentoring to help them build confidence and proficiency.
The role
also involves updating course content to reflect current industry standards, supporting learners with doubts and queries, and collaborating with the institute’s academic team to improve training quality and outcomes. The trainer is expected to maintain a professional, inclusive, and supportive classroom environment that encourages active participation and continuous learning.
Qualifications
- Strong proficiency in Python programming, including core syntax, data structures, functions, modules, and object-oriented programming.
- Experience with commonly used Python libraries and tools (e.g., NumPy, pandas, matplotlib, Jupyter Notebook) and familiarity with basic data analysis workflows.