
Data Structures and Algorithms Trainer
11 hours ago
**Responsibilities**:
- Develop and deliver comprehensive training programs on data structures and algorithms.
- Create and maintain course materials, including lecture notes, assignments, and assessments.
- Provide hands-on coding sessions and real-world examples to enhance learning.
- Assess student progress and provide constructive feedback.
- Stay updated with the latest trends and advancements in data structures and algorithms.
- Foster a positive and engaging learning environment.
- Collaborate with other trainers and team members to continuously improve the curriculum.
**Requirements**:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Extensive experience in programming with C, C++, and Python.
- In-depth knowledge of data structures and algorithms.
- Proven teaching or training experience, preferably in a classroom or corporate setting.
- Excellent communication and presentation skills.
- Ability to explain complex concepts in a clear and understandable manner.
- Strong problem-solving skills and a passion for teaching and mentoring.
- Willingness to travel and conduct onsite training sessions.
**Preferred Qualifications**:
- Experience with competitive programming or algorithmic competitions.
- Published work or contributions to open-source projects related to data structures and algorithms.
- Familiarity with online teaching tools and platforms.
**Job Types**: Part-time, Temporary, Freelance
Contract length: 3 months
Pay: From ₹50,000.00 per month
**Benefits**:
- Commuter assistance
- Flexible schedule
- Food provided
- Internet reimbursement
Schedule:
- Day shift
- Fixed shift
- Monday to Friday
- Weekend availability
Supplemental pay types:
- Commission pay
- Overtime pay
Ability to commute/relocate:
- Noida, Uttar Pradesh: Reliably commute or willing to relocate with an employer-provided relocation package (preferred)
**Experience**:
- total work: 2 years (preferred)
- total: 3 years (preferred)
Work Location: In person
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