Novartis Recruitment 2026 is hiring Data Science Interns in India for an opportunity to work on real-world workforce and business analytics problems. The role is suitable for candidates with a graduate or postgraduate degree in a quantitative discipline and relevant exposure to data science, statistics, machine learning, predictive analytics, and AI.
Interns will work on areas such as employee engagement, recruitment optimization, workforce planning, generative AI, and LLM-based use cases, while collaborating with stakeholders on practical data-driven solutions.
 |
| Novartis Data Science Intern Freshers Hiring 2026 India |
Job Overview
Company: Novartis
Job Role: Intern – Data Science
Job ID: REQ-10087679
Experience: Freshers / Internship
Education: Graduate or Postgraduate Degree
Discipline: Quantitative / Data Science-related field
Job Type: Internship
Location: India
Work Mode: Not specified in the provided job description
Salary: ₹4–5 LPA (Expected)
Application Mode: Online
About Novartis Company
Novartis is a global pharmaceutical and healthcare company focused on developing medicines and using science and technology to address complex healthcare challenges.
This Data Science Internship provides exposure to the use of analytics, statistical modelling, machine learning, and generative AI in workforce-related business problems.
About Role
The Data Science Intern will work on projects involving both structured and unstructured data. The role combines statistics, machine learning, data analysis, visualization, and generative AI to generate insights that can support workforce and business decisions.
The internship provides an opportunity to work on practical use cases such as talent acquisition, employee experience, workforce planning, location strategy, and HR workflow optimization.
Is your resume ATS-friendly?
🚀 Build ATS Resume NowKey Responsibilities
As a Data Science Intern, you will:
- Apply data science techniques to real-world business challenges.
- Work on employee engagement and recruitment optimization use cases.
- Develop predictive models for workforce planning.
- Design analytical models, dashboards, and frameworks.
- Conduct data mining and exploratory data analysis (EDA).
- Perform feature engineering to identify actionable insights.
- Apply statistical and machine learning techniques.
- Work with regression, classification, clustering, and statistical inference.
- Develop visualizations and self-service dashboards.
- Explore generative AI applications for HR workflows.
- Prototype LLM-based workforce analytics use cases.
- Research and support the development of new algorithms and statistical models.
- Analyze structured and unstructured data.
- Collaborate with supervisors, stakeholders, and business leaders.
Eligibility Criteria
- Graduate or postgraduate degree in a quantitative discipline.
- Relevant experience or academic exposure to Data Science.
- Strong foundation in statistics and machine learning.
- Candidates interested in applying data science to real-world business problems.
- Ability to work with structured and unstructured data.
- Freshers with relevant academic/project experience can consider this opportunity.
Important: The provided JD mentions graduates/postgraduates from a top-tier university. Candidates should verify the complete eligibility criteria in the official listing before applying.
Required Skills
- Statistical Modeling
- Machine Learning
- Regression
- Generalized Linear Models (GLM)
- Non-linear Regression
- Classification
- Decision Trees
- Random Forest
- Boosting
- Support Vector Machines (SVM)
- CART
- Clustering
- Design of Experiments
- Statistical Inference
- Data Mining
- Exploratory Data Analysis (EDA)
Is your resume ATS-friendly?
🚀 Build ATS Resume NowPreferred Skills
The provided job description does not list a separate preferred-skills section. However, exposure to the following areas would align well with the responsibilities mentioned in the role:
- Generative AI
- Large Language Models (LLMs)
- Predictive Workforce Analytics
- HR Analytics
- Dashboard Development
- Business Analytics
- AI-based workflow optimization
- Working with structured and unstructured data
Why Join
- Work on real-world data science problems.
- Gain exposure to machine learning and predictive analytics.
- Explore practical applications of generative AI and LLMs.
- Work on workforce analytics and business decision-making.
- Build dashboards and predictive models used for stakeholder insights.
- Collaborate with experienced professionals and business stakeholders.
- Gain practical experience across statistics, ML, and AI.
Job Location
India
The specific city/work arrangement is not clearly mentioned in the provided job description. Candidates should check the official Novartis listing for the latest location details.
Expected Salary
₹4–5 LPA (Expected)
The provided job description does not state an official salary figure. Therefore, ₹4–5 LPA should be treated as an estimated salary range, not an official Novartis compensation figure.
Selection Process
The exact selection process is not specified in the provided job description.
Candidates should be prepared for potential discussions or assessments covering:
- Resume/application screening
- Statistics and machine learning fundamentals
- Data science/project discussion
- Technical interview
- Business problem-solving or case-based questions
- HR/final discussion
The actual recruitment process may differ.
How to Apply
Interested candidates can apply through the official Novartis Careers website.
Official Apply Link: Apply for Novartis DS Intern Role
Is your resume ATS-friendly?
🚀 Build ATS Resume NowImportant Note While Applying
- Carefully check the education and university requirements before applying.
- Keep your resume focused on Data Science, Statistics, Machine Learning, AI, and relevant academic projects.
- Mention practical projects involving regression, classification, clustering, EDA, feature engineering, or predictive modelling.
- If you have worked on an LLM or Generative AI project, highlight it clearly.
- Be prepared to explain your projects, including the dataset, methodology, model selection, evaluation, and results.
- The salary mentioned above is an expected estimate and is not confirmed in the provided JD.
- Verify the latest eligibility, location, and application status on the official Novartis Careers page before submitting your application.
- FreshHire Daily only shares job opportunities from company career portals or trusted recruitment sources. We do not charge any fee for job applications or recruitment.
Basic Interview Questions
- Tell me about yourself and your Data Science background.
- What is the difference between supervised and unsupervised learning?
- Explain linear regression and when you would use it.
- What is the difference between regression and classification?
- What is a Random Forest?
- What is overfitting and how can you prevent it?
- Explain clustering with an example.
- What is feature engineering?
- What is exploratory data analysis (EDA)?
- What is statistical inference?
Related Jobs
- American Express Analyst – Data Analytics
- Deloitte Global Data Management – Data Validation
- Signzy Associate Business Analyst
- Franklin Templeton Associate Software Engineer
- mthree Graduate Recruitment Program
Disclaimer
This job information is shared for educational and informational purposes only. We are not recruiters or affiliated with Novartis. Salary figures are estimates where explicitly mentioned as expected and may differ from the actual offer. Candidates should verify eligibility, location, compensation, and recruitment status through the official Novartis Careers website before applying.
0 Comments