Data Analyst

Overview

Fam is looking for a Data Analyst to dig into data, find insights and turn complex datasets into product and business decisions, working closely with Product, Engineering, Business and Finance teams.

What you'll do

• Extract, analyse and interpret data to answer product and business-related questions.
• Work closely with Product Managers to evaluate product performance and identify improvement opportunities.
• Analyse user behaviour, funnels, cohorts and key business metrics.
• Build and maintain dashboards and reports to track important metrics.
• Identify trends, patterns and anomalies and proactively highlight areas that need attention.
• Support data-driven decision-making through actionable insights and recommendations.
• Collaborate with cross-functional teams to understand business problems and provide analytical support.
• Leverage AI tools to streamline analysis, automate workflows and improve efficiency.
• Work on ad-hoc analysis and projects across different teams as business needs evolve.

What you'll need

• Bachelor's degree in Engineering, Economics, Statistics, Mathematics or another quantitative field.
• Strong SQL skills with experience writing complex queries involving joins, CTEs and window functions.
• Ability to independently extract, clean, structure and analyse large datasets.
• Strong analytical and problem-solving skills with an eye for identifying trends and patterns.
• Ability to interpret data and translate findings into meaningful business and product insights.
• Understanding of key product and business metrics.
• Comfortable using AI tools to improve analytical workflows, write and optimise queries, automate repetitive tasks and explore new ways of solving problems.
• Strong communication skills and the ability to work with multiple stakeholders.
• A proactive approach with the ability to take ownership of problems and drive them to closure.

Nice to have

• Experience working in fintech, consumer internet or high-growth startups.
• Familiarity with tools such as Metabase, Looker, Mixpanel or Amplitude.
• Working knowledge of Python and Excel.
• Exposure to A/B testing, cohort analysis and funnel analysis.
• Experience working with large-scale databases such as BigQuery, Redshift or ClickHouse.
• Experience experimenting with AI-powered analytics tools and workflows.