Middle Product Analyst (Product Department)

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. You’ll help bring more structure to how we discover growth opportunities, validate product hypotheses, and turn user behavior data into meaningful product improvements.
You’ll 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.

Who We Are

StellarTech is an EdTech company building scalable digital products that help people learn, grow, and access new opportunities. We operate at the intersection of product, technology, and data, creating learning experiences for a global audience.
Our team is focused on building sustainable products and making better decisions through a deep understanding of users, business metrics, and product performance.

What You’ll Do

• Translate user behavior into clear, actionable recommendations and help product teams make data-driven decisions.
• Support product hypotheses with data: validate ideas, evaluate feature impact, and help prioritize the roadmap with evidence.
• Analyze funnels, retention, activation, monetization, and other key product metrics to identify growth opportunities and product risks.
• Design and evaluate A/B tests: help frame the research question, define success metrics, estimate sample sizes, monitor experiment performance, and interpret outcomes.
• Create, maintain, and evolve dashboards, alerts, and analytical tools used by product teams for day-to-day decision-making.
• Contribute to AI-assisted analytics workflows that help product teams test hypotheses faster, access relevant metrics more easily, and turn data into product decisions with less manual effort.

What We Expect

• 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.

Nice to Have

• 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.

Why You’ll Love Working With Us

• Meaningful product work: You’ll 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: We provide access to AI subscriptions and modern tools to help you work faster, automate routine tasks, and focus on higher-impact analytical work.
• Health support: We offer medical expense compensation.
• Work-life balance: You’ll have flexible paid time off, including 21 days of annual leave plus 10 bank holidays.
• Collaborative culture: You’ll work with product-minded, curious, and driven people who value ownership, clear communication, and data-driven decisions.

Hiring Process

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