We are seeking a highly analytical and detail-oriented Data Analyst to join our team. In this role, you will be instrumental in analysing our vast data sets to derive insights that drive decision-making across various departments including Business, Marketing, and Operations.

Key Responsibilities:

• Collaborate with the tech and product team to define key performance indicators (KPIs) for the product.

• Design and implement robust metric tracking systems, ensuring consistent and accurate data collection.

• Design A/B tests and other experiments to validate product hypotheses. Analyse results to provide insights on product changes and their impact on user behaviour.

• Generate product insights from data analyses to suggest new features or improvements.

• Bridge the gap between data and product by translating findings into actionable product strategies.

• Dive deep into the data to determine the root causes of observed patterns or anomalies.

• Identify key drivers influencing metrics and advise on potential interventions.

• Conduct ad-hoc analyses to answer specific business questions or to inform product strategy. • Create clear and impactful visualizations that convey complex data insights.

• Collaborate with stakeholders to communicate findings, provide recommendations, and influence product direction.

Required Skills:

• Strong proficiency in Python or R.

• Demonstrated experience in SQL (experience with other data storage technologies is a plus).

• Mastery of statistical hypothesis testing, experiment design, and causal inference techniques. • Hands-on experience with A/B and multivariate testing methodologies.

• Familiarity with behavioural data and experimentation platforms such as Mix panel, and Growth Book.

• Strong visual, written, and verbal communication skills and ability to convey complex analytical results to non-technical audiences. Preferred Requirements:

• Familiarity with ML algorithms and techniques, including but not limited to regression models, clustering, and classification.

• Expertise in building, evaluating and deploying ML models.

• Experience in e-commerce, marketplace business-models, and proficiency in digital marketing.