Middle Product Analyst

Role Description

We’re looking for a Middle Product Analyst to join our growing Product Analytics team. In this role, you’ll contribute to end-to-end product analytics — from event tracking and data quality to funnels, experimentation, dashboards, and actionable insights.

• Help bring more structure to how we discover growth opportunities, validate product hypotheses, and turn user behavior data into meaningful product improvements.
• Work closely with product managers, fellow analysts, and data engineers to help product teams better understand user behavior, measure product performance, and make data-driven decisions.

Qualifications

• 3+ years of experience as a Product Analyst or Data Analyst in a product-led tech company. Experience with B2C platforms, SaaS, or marketplaces is a plus.
• Strong SQL skills and confidence working with large datasets.
• Hands-on experience with product analytics tools such as Amplitude, Mixpanel, GA4, or similar, and BI tools such as Tableau, Looker, Power BI, or similar.
• Solid understanding of product metrics: activation, retention, conversion, funnels, monetization.
• Experience with A/B testing and a working knowledge of statistics for experiment evaluation.
• Ability to turn ambiguous product questions into structured analyses and clear recommendations.
• Strong communication skills: ability to explain findings clearly to both technical and non-technical stakeholders.

Requirements

• Python or R for analysis and automation of recurring insights.
• Experience using AI tools to accelerate product analytics workflows.
• Proactive, problem-solving mindset — comfortable with ambiguity in a fast-paced, evolving environment.

Benefits

• Meaningful product work: Help build scalable EdTech products that support real users and influence how people learn and grow.
• Remote-first setup: We’re a global remote team, with regular overlap for collaboration.
• AI-enabled workflow: Access to AI subscriptions and modern tools to help you work faster, automate routine tasks, and focus on higher-impact analytical work.
• Health support: Medical expense compensation.
• Work-life balance: Flexible paid time off, including 21 days of annual leave plus 10 bank holidays.
• Collaborative culture: Work with product-minded, curious, and driven people who value ownership, clear communication, and data-driven decisions.

Hiring Process

• Recruiter Screening — a short call to get to know each other and discuss your experience, expectations, and role details.
• Technical Interview — a product analytics interview focused on SQL, metrics, experimentation, and analytical thinking.
• Hiring Manager Interview — a final conversation about team fit, role expectations, product context, and how we can work effectively together.