Data Scientist

As a Data Scientist on the QC Hub team, you’ll be the analytical brain behind one of the company's fastest-growing verticals. You won’t just crunch numbers — you’ll partner directly with product and business leaders to shape strategy, design experiments that affect millions of users, and build the data foundations that power smarter decisions. This is a role for someone who loves turning messy, ambiguous business questions into clean, actionable analysis — and who gets energy from seeing their insights change how a team operates.

What You’ll Actually Do
You’ll spend roughly:

• 40% on deep analysis and experimentation — designing A/B tests, running multivariate experiments, doing deep dives into performance drivers, and turning findings into clear recommendations.
• 30% on data modelling and quality — building and maintaining the data models that let us measure what matters, profiling source data, and ensuring data reliability.
• 30% working with stakeholders — partnering with product and business managers to frame the right questions, set meaningful KPIs, and present insights that drive action.

Day-to-day, you’ll:

• Turn ambiguous business questions into structured analytical problems
• Build and maintain dimensional data models in BigQuery
• Design, execute, and interpret experiments (A/B and multivariate)
• Create automated dashboards and reports that stakeholders actually use
• Challenge assumptions with data — including your own
• Collaborate with data engineers on logging and data pipeline quality

What You Bring
Degree in a quantitative field (statistics, mathematics, economics, computer science, engineering, or similar) — or equivalent practical experience. A postgraduate degree is a plus but not required.

Must-Haves:

• Strong SQL skills — you can write complex queries with window functions, CTEs, and optimise for performance on large datasets
• Reproducible analysis in Python or R — you write clean, well-structured analytical code, not one-off scripts
• Experiment design expertise — you understand when to use A/B vs. multivariate tests, can calculate sample sizes, and know the pitfalls of statistical testing
• Full analysis lifecycle experience — from problem framing through data auditing, analysis, interpretation, and presenting recommendations
• Data modelling knowledge — you understand dimensional design and can build models that serve both ad-hoc analysis and automated reporting
• Product analytics intuition — you’re familiar with metrics like conversion, engagement, and retention, and know how to measure product health
• 3+ years in data science, analytics, or a related quantitative field

Nice-to-Haves:

• Experience with BigQuery and Google Cloud Platform
• Data engineering skills (Airflow, dbt, or similar pipeline tools)
• Experience with ML frameworks (Scikit-learn, XGBoost, LightGBM)
• Familiarity with modern data tools and AI-assisted analysis workflows
• Experience in an online consumer product or marketplace environment

Location
Dubai, United Arab Emirates