Data science intern

Data Science Intern

Join our data science team as an intern and get hands-on with the messy, real-world problem of turning fragmented marketing and product data into decisions. You'll work directly under a Senior Data Scientist, ship a real dashboard used by the team, and leave the internship with production-grade portfolio work.

Why this role exists

Our marketing and product data currently live in disconnected systems, which makes it hard to answer a question that matters a lot to the business: which acquisition channels bring in our most engaged users? You'll help stitch those sources together and build the first prototype that maps marketing touchpoints to product engagement, so the team can make sharper decisions about where to invest.

What you'll do

Data discovery and mapping. Work alongside the Senior Data Scientist to inventory our scattered marketing and product data sources, understand what each one contains, and document how they relate.

Data cleaning and consolidation. Use Python and SQL to clean, join, and reshape fragmented datasets into a single analysis-ready table. This is where most of the learning happens — real data is never as tidy as coursework data.

Dashboard build. Design and ship an interactive dashboard that visualizes how marketing channels connect to user engagement metrics. Iterate with your mentor on what to show and how to show it.

Documentation. Write down your data cleaning steps, assumptions, and pipeline logic so the team can maintain and extend your work after the internship ends.

What we're looking for

Working knowledge of Python for data manipulation (Pandas or similar).

Comfortable writing SQL queries — joins, aggregations, filtering.

Exposure to data visualization tools (Power BI, Tableau, or Python libraries like Matplotlib / Seaborn / Plotly).

Curiosity and comfort asking questions in a collaborative team setting.

Currently pursuing or recently completed a bachelor's degree in Computer Science, Data Science, Statistics, or a related technical field.

Nice to have

Familiarity with Git for version control.

Prior exposure to Pandas beyond introductory tutorials.

Basic statistics — understanding of distributions, averages vs medians, and simple hypothesis testing.

What success looks like

By the end of the internship you will have delivered a consolidated data prototype and an interactive dashboard that maps marketing channels to user engagement metrics. Success means your data cleaning steps are documented, the marketing-to-product joins are verified for accuracy, and the team can act on what the dashboard shows.

Logistics

Hybrid role based in Jizah, Egypt. Internship position reporting to a Senior Data Scientist on a small (2-5 person) data science team. Application deadline: 30 August 2026.

Benefits

1-on-1 mentorship from a Senior Data Scientist

Portfolio-ready project you can point to after the internship

Hybrid working setup