About the role
You will help client teams decide what to do next: which customers are about to leave, whether a new feature worked, what demand will look like next month. You combine statistics, modelling and clear communication, which is the mix data science hiring managers look for.
Roles and responsibilities
- Audit data quality and document every assumption you make
- Run exploratory analysis and surface patterns that matter
- Design and analyse A/B tests with the right statistical tests
- Build predictive and forecasting models and evaluate them fairly
- Explain model behaviour with tools like SHAP
- Write SQL to pull and shape the data you need
- Present recommendations in a short report a manager can act on
By the end, you will be able to
- Go from a business question to a defensible, data-backed answer
- Choose and apply the right statistical test
- Build churn, segmentation and forecasting models
- Communicate uncertainty without hiding behind jargon
- Build a portfolio of real case studies
Questions you will be able to answer
How do streaming apps know which show you will binge next?
Did that new feature really increase sales, or was it just a good week?
How can a store predict Diwali demand months in advance?
Why do averages sometimes lie, and what should you use instead?
What you might build
- A churn-driver analysis for a subscription app
- An A/B test readout with a recommendation
- A demand forecast with backtesting
Every intern gets different tickets. These are examples of the kind of work, not a fixed list.
How the first three months progress
Week 1
Onboarding & data toolkit
Git & notebooks, pandas, data sources, project structure
Week 4
Hypothesis testing & A/B tests
t-test, chi-square, p-values & power, experiment design, business recommendation
Week 8
Clustering & segmentation
RFM analysis, k-means, persona profiles, marketing actions
Week 12
Capstone delivery
end-to-end analysis project, model + insights, report, presentation
Four- and six-month internships add advanced specialisation, a major client project, open-source work and interview preparation.
Tools you will use
Who should apply
- Basic Python or willingness to pick it up fast
- Comfortable with school-level statistics and maths
- Enjoy asking "why" about numbers