Product Analyst

Role overview

This opportunity is presented on behalf of a partner organization that handles the application review and all subsequent hiring steps. The hiring company is seeking a Product Analyst located in Germany.

In this role, you will help shape product decisions by converting user activity and platform data into practical insights that inform roadmap direction and product strategy. Your analysis will focus on how customers use a complex SaaS platform, where they encounter friction, what drives adoption, and which behaviors support retention.

You will work closely with product leadership and cross-functional partners to make sure decisions are backed by evidence rather than assumptions. The position is highly analytical, fast-paced, and visible to senior stakeholders, with a strong emphasis on improving product intelligence across the business.

This role is a strong fit for someone who enjoys deep analytical work and wants to see their findings directly influence product improvements and business outcomes.

Key accountabilities

• Take ownership of user-behavior analysis across the product, including customer journeys, engagement trends, session depth, and usage frequency by segment.
• Evaluate feature performance, adoption levels, and experiment outcomes to understand what increases or limits product value.
• Run cohort, funnel, retention, and expansion analyses to spot behavioral patterns and anticipate customer lifecycle results.
• Detect friction points, drop-offs, and weak-performing areas, then convert those findings into structured recommendations.
• Define, monitor, and maintain essential product KPIs while keeping reporting consistent, accurate, and dependable.
• Provide ongoing analytical support to product leadership to help guide roadmap choices and flag potential product-health risks early.

Requirements

• At least 3–6+ years of experience in product analytics, SaaS analytics, or another data-driven product setting.
• Advanced ability in SQL, data modeling, and analytics tooling, plus practical experience handling large datasets.
• Hands-on background in cohort analysis, funnel analysis, retention modeling, and interpretation of behavioral data.
• Ability to turn complex information into concise, executive-ready insights that shape product decisions.
• Experience partnering with Product Managers and other cross-functional teams in high-growth environments.
• Strong quantitative judgment, organized thinking, and comfort working with incomplete or changing data.
• Ability to thrive in fast-moving, product-led organizations where analytics directly influences execution.

Benefits

• Compensation that is competitive and aligned with both experience and market standards.
• A fully remote setup with the chance to collaborate across global teams.
• Flexible work arrangements designed to support a healthy work-life balance.
• Direct exposure to senior product leaders and participation in roadmap discussions.
• Opportunity to work with large-scale SaaS product analytics and strategic decision-making.
• A dynamic, high-growth environment centered on data-led innovation.

Data privacy and hiring process

Applications are reviewed through an AI-supported matching process designed to assess fit quickly, fairly, and objectively against the role’s key requirements. The strongest matches are shortlisted and passed on to the hiring company, while the employer’s internal team manages final decisions and next steps such as interviews or assessments.

By applying, you acknowledge that your personal data may be processed to assess your candidacy and shared with the hiring employer in line with applicable data protection laws, including GDPR. This processing is based on legitimate interest and pre-contractual measures, and you retain the right to request access, correction, deletion, or objection at any time.

AI tools may also be used to support parts of recruitment, including resume review, response analysis, and spotting possible inconsistencies or verification signals in application materials. These tools assist the recruiting team but do not replace human judgment, and final hiring decisions are made by people.