We are looking for a curious and analytical Business Analyst who can work with large datasets, translate business questions into structured analyses, and turn insights into actionable recommendations.
The role will work closely with Commercial, Marketing, Operations, Product, and other teams to evaluate performance, identify opportunities, and support data-driven decisions.
Strong hands-on SQL skills are essential, along with an interest in using AI to make analytics faster and more scalable.
- Analyse business performance across growth, customer behaviour, revenue, profitability, marketing, and operations.
- Independently write and optimise SQL queries to extract and analyse large datasets.
- Conduct deep dives to identify trends, performance gaps, growth opportunities, and key business drivers.
- Analyse customer behaviour across acquisition, retention, churn, frequency, cohorts, and segmentation.
- Support business cases, forecasting, scenario modelling, and impact estimation for new initiatives.
- Build dashboards and recurring reports using BI and visualisation tools.
- Partner with cross-functional teams to define KPIs and provide clear, commercially relevant recommendations.
- Ensure accuracy and reliability of analytical outputs.
AI in Analytics
- The candidate should actively use AI as part of the analytics workflow, including:
- Accelerating SQL development, debugging, and analysis.
- Structuring analytical approaches and generating hypotheses.
- Automating repetitive reporting and analytical tasks.
- Improving insight generation, documentation, and stakeholder communication.
AI should enhance analytical thinking, not replace it.
- 3-5 years of experience in Business Analytics, Data Analytics, Strategy Analytics, Growth Analytics, or a related field.
- Strong hands-on SQL skills.
- Strong Excel / Google Sheets skills.
- Experience with BI tools such as Tableau, Power BI, Looker, Metabase, or similar.
- Strong analytical, problem-solving, and structured thinking skills.
- Ability to translate data into clear business recommendations.
- Comfortable working with multiple stakeholders in a fast-paced environment.
- Practical exposure to generative AI tools in analytical workflows.
Nice to Have
- Experience in e-commerce, marketplaces, quick commerce, retail, fintech, or consumer technology.
- Exposure to Python.
- Understanding of A/B testing and experimentation.
- Experience with customer lifecycle, marketing, pricing, retention, churn, or unit economics.