Data Science Instructor - Learning Centre

Start Date

Starts Immediately

CTC (ANNUAL)

Competitive salary Competitive salary

Experience

1 year(s)

1 year(s) experience

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Not Provided

Posted 1 week ago

Job

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About the job

Job Title: Instructor Offline Learning Centre

Location: Amritsar

Working Days: 6 (Monday Saturday)

About upGrad

Founded in 2015, upGrad is Asias largest integrated Learning, Skilling, Workforce Development, and Placement company. Its offerings include online and hybrid degrees, study abroad programs,

certifications, bootcamps, and doctorates for working professionals. Through its B2B arm, upGrad

also provides enterprise training, recruitment, and staffing services. With 10M+ learners across 100+countries, 300+ global university partners, 2500+ pathway connections, and 20,000+ recruitment partners, upGrad continues to empower careers worldwide.

Learn more:

About the Role

As an Instructor at our Offline Learning Centres, you will deliver engaging sessions in Data Science,

Machine Learning, Deep Learning, and related fields to students and working professionals. You will play a vital role in ensuring high-quality learning outcomes through classroom teaching, mentorship, and academic support. This is a unique opportunity to combine your passion for technology and education, while shaping the careers of tomorrow.

6 Reasons to Join upGrad Offline Learning Centres

1. Career Growth & SME Pathway: Accelerate your career with opportunities to move into

leadership roles and grow as a Subject Matter Expert by contributing to content

development, curriculum design and new program launches.

2. Continuous Upskilling : Access 100% free upGrad programs for yourself and a 50% discount

for your family.

3. Comprehensive Health & Wellbeing : Benefit from INR 5L medical insurance for yourself

and your family, plus a 24x7 mental health helpline for all-round support.

4. Attractive Incentives: Earn additional incentives for successful student referrals from your

batches, giving you direct rewards for expanding the learner community.

5. Employee Referral Bonus: Receive INR 15,000 for every successful employee referral

bring great talent to upGrad and get rewarded.

6. Impact & Exposure: Opportunity to work with industry leaders, design cutting-edge content,

and directly impact learner success.

Key Responsibilities

* Deliver in-person lectures and training sessions in Data Science, Machine Learning, Deep

Learning and related domains.

* Guide learners through concepts, case studies, and projects to ensure strong understanding

and application.

* Collaborate with Centre Managers and academic teams to monitor learner progress and

outcomes.

* Support students with doubt-solving, mentorship, and building career-ready skills.

* Continuously update knowledge and content to stay current with industry trends and tools.

Skills & Experience

* Minimum 1+ years of teaching/training experience in Data Science, Machine Learning, or

related fields.

* Strong programming skills in Python and understanding of SQL, Excel.

* Solid grasp of ML/DL concepts such as Regression, Decision Trees, Random Forests,

Ensemble methods, Neural Networks, NLP, Recommendation Systems, etc.

* Strong communication, presentation, and mentoring skills.

* Comfortable with both classroom delivery and online teaching (camera-facing).

* Education: BE/ B.Tech (minimum); Postgraduate preferred.

Equal Opportunity

We are an equal opportunity employer and value diversity at our company.

We do not discriminate on the basis of race, religion, colour, national origin, gender, gender identity or expression, sexual orientation, age, marital status, veteran status, or disability status.

All employment is decided on the basis of qualifications, merit, and business need.

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Who can apply

Only those candidates can apply who:

1. have minimum 1 years of experience

Salary

Probation:

Duration:

Salary during probation:

After probation:

Annual CTC: Competitive salary

Number of openings

Editor’s note

Information above is Internshala's interpretation and paraphrasing of what we found on the shared link.