Novartis Internship 2026 | Intern Data Science | Hyderabad

Introduction

Novartis is offering an Intern – Data Science opportunity in Hyderabad, India, for candidates interested in applying data science, statistics, machine learning, and generative AI to real-world business problems. The position is part of the People & Organization / Human Resources function and is listed as an Early Career, Fixed-Term, full-time role. The job was posted on September 9, 2026, under Job ID REQ-10087679.

This opportunity may suit students and recent graduates who want practical exposure to predictive analytics, workforce analytics, dashboards, and emerging AI technologies. Candidates should carefully review the official requirements before applying.

1) Job Summary

Company: Novartis Healthcare Private Limited
Position: Intern – Data Science
Job ID: REQ-10087679
Location: Hyderabad, India
Work Mode: Office-based
Employment Type: Full-time, Early Career (Fixed Term)
Business Unit: Human Resources
Division: People & Organization
Functional Area: Others

The intern will work on data science problems involving areas such as employee engagement, recruitment optimization, predictive workforce planning, and generative AI. The role also involves developing models, dashboards, frameworks, and analytical solutions that can support business decisions.

2) Job Description

As a Data Science Intern at Novartis, candidates will have an opportunity to apply quantitative and analytical skills to practical workforce-related challenges. The role includes working with both structured and unstructured data and supporting research and development of algorithms, statistical models, and business models.

Key responsibilities may include:

Applying statistical and machine-learning techniques to business problems.
Working with methods such as regression, classification, clustering, and design of experiments.
Developing predictive models for areas such as talent acquisition, employee experience, location strategy, and workforce planning.
Performing data mining, exploratory data analysis (EDA), and feature engineering.
Creating dashboards and visualizations that help stakeholders understand data and make informed decisions.
Exploring generative AI and large language model (LLM) applications for workforce analytics.
Supporting the development of new algorithms, statistical approaches, and analytical methods.
Collaborating with stakeholders and presenting insights from data.

The position therefore combines data science fundamentals with business problem-solving and emerging AI applications.

3) Eligibility Criteria

According to the job posting, Novartis is looking for candidates with relevant experience in data science and a graduate or postgraduate qualification from a top-tier university in a quantitative discipline. The posting specifically highlights statistical modeling and machine learning expertise.

Important technical areas include:

Regression, including GLM and nonlinear techniques
Classification
Decision trees and Random Forest
Boosting
SVM and CART
Clustering
Design of experiments
Statistical inference
General statistical modeling and machine learning

Who Should Apply?

This role could be a good match for candidates who:

Have an academic background in a quantitative discipline.
Have studied or worked on data science or machine learning projects.
Understand statistical modeling and inference.
Can analyze datasets and communicate meaningful findings.
Are interested in applying AI and analytics to business problems.
Want practical exposure to LLMs and generative AI.
Can work collaboratively with business stakeholders.

Who May Not Be a Good Fit?

The role may be less suitable for candidates who have little interest in statistics or quantitative analysis, are unfamiliar with fundamental machine-learning concepts, or prefer purely software-development roles without substantial analytical work.

Applicants should also avoid claiming skills they cannot demonstrate. The selection process may assess whether the candidate’s technical knowledge matches the requirements of the position.

4) What Should Be Highlighted in the Resume?

Candidates should tailor their resume to the requirements rather than simply listing every technology they have encountered.

Consider highlighting:

Data science and machine-learning projects
Statistical modeling experience
Regression and classification projects
Clustering or predictive analytics work
Exploratory data analysis and feature engineering
Dashboard and data-visualization projects
Generative AI or LLM-related projects
Research work involving statistical methods
Academic projects using real-world datasets
Relevant programming, analytics, or data tools you can confidently demonstrate

Where possible, describe what you built, what problem you solved, what methodology you used, and what result you achieved.

5) What Candidates Should Expect During Recruitment Process? (Selection Process)

The exact selection stages for this particular internship are not specified in the job posting, so candidates should not assume a fixed number of interview rounds.

A typical hiring process may involve application screening followed by one or more assessments or interviews, depending on the position and recruiting team. For a data science internship, candidates should be prepared to discuss their academic background, projects, statistical concepts, machine-learning methods, analytical reasoning, and experience working with data.

Candidates should also be ready to explain their projects clearly rather than relying only on technical terminology.

6) About the Company

Novartis is an innovative medicines company focused on reimagining medicine to improve and extend people’s lives. According to the company’s website, its medicines reach 296 million people worldwide.

Novartis operates across areas including research and development, healthcare, data and digital functions, operations, and other global business functions. Its career opportunities include roles for students, graduates, and experienced professionals.

7) Why Join This Company?

For candidates interested in data science, this internship offers an opportunity to apply quantitative skills to business challenges rather than working only on theoretical exercises.

Potential learning areas include:

Practical predictive analytics
Workforce and people analytics
Statistical modeling
Machine learning
Data visualization
Generative AI
LLM-based applications
Stakeholder collaboration

The role also provides exposure to projects with visibility among stakeholders and leaders, according to the official job description.

8) Frequently Asked Questions (FAQ)

Q1. What is the position offered by Novartis?
The position is Intern – Data Science, Job ID REQ-10087679.

Q2. Where is the internship located?
The position is based at the Novartis Hyderabad office in India.

Q3. Is this a full-time position?
Yes. The listing identifies it as a full-time, early-career fixed-term opportunity.

Q4. What educational background is preferred?
The posting asks for a graduate or postgraduate background from a top-tier university in a quantitative discipline, along with relevant data science experience.

Q5. Which technical skills are important?
Statistical modeling, machine learning, regression, classification, clustering, design of experiments, and statistical inference are specifically highlighted.

Q6. Does the role involve generative AI?
Yes. The job description specifically mentions generative AI and LLM-based use cases for workforce analytics.

Q7. Where can candidates apply?
Candidates should use the official Novartis career listing for the application and verify the requirements before submitting their details. View the official Novartis job posting

The Apply link is available in the “How to Apply?” section.

Note: This article is intended for informational purposes. Job requirements, availability, and recruitment procedures can change, so applicants should rely on the official Novartis careers page for the latest information. Novartis also warns candidates about fraudulent job offers and states that it does not make job offers without an interview or ask candidates for money.

How to Apply?

Interested candidates meeting the eligibility criteria have to apply at the following link: