Product Analyst – Partner Journey

Product Analyst – Partner Journey

Simplify complexity
and shape the experience of tens of thousands of partners

How do you make our customers happy?

At bol, our customers rely on a platform that offers everything they need — reliably, quickly, and seamlessly. Behind the scenes, this depends on the thousands of partners who sell on bol. As a Product Analyst in the Partner Journey domain, you’ll help make their experience frictionless and scalable — so they can focus on growing their business and delivering value to customers. Your insights will help product teams build tools that are intuitive, impactful, and grounded in real needs — turning complexity into clarity.

The biggest challenge

Selling on a platform should feel simple. But making it simple? That’s where the complexity lies. Every partner is different — from solo sellers to global brands — and every step of their journey can present unique hurdles. Your challenge is to cut through this complexity with data: identifying the friction points that matter most, separating signal from noise, and guiding the team toward high-impact decisions that improve both experience and business outcomes.

What you’ll do as Product Analyst

You’ll join the Data, Analytics & AI (DAAI) department — bol’s engine for scaling data-driven decisions — while being embedded in a cross-functional product team.

In this role, you will:

• Partner with Product Managers to define and track OKRs and build visualizations that make progress visible and actionable.
• Design and own metrics that align with user and business outcomes, ensuring product teams stay focused on what matters.
• Dig deep into behavioral and business data to uncover patterns, surface opportunities, and shape product strategy.
• Translate complex findings into clear, actionable insights that influence prioritization and product direction.
• Design experiments and apply causal inference techniques (e.g. A/B testing, difference-in-differences) to validate hypotheses.
• Measure and explain the impact of product changes post-launch — learning fast and iterating often.
• Build and maintain scalable data models and dashboards that power your team with reliable, self-serve insights.
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To do this, you'll need:

• Fluency in SQL, Git, dbt, and solid statistics fundamentals.
• Comfort with tools like Python, Looker, BigQuery, Airflow, and Jupyter Notebooks.
• A strong grasp of product development frameworks — and the pragmatism to know where analytics fits in.
• Experience with advanced analytics methods that establish causal relationships.
• A high degree of autonomy, a bias for action, and a sharp eye for what really matters.
• The ability to influence without authority, build trust quickly, and drive clarity in cross-functional teams.
• A deep respect for data quality and analytics best practices — because credibility matters.

Why you can make the difference

Because you care what happens after the analysis. You don’t just hand off dashboards — you stay in the conversation, challenge assumptions, and help your team make smarter, faster, and more focused decisions. You’re excited by ambiguity, energized by impact, and you know that in a platform this complex, data is only useful if it leads to clarity and action. You think in systems, move with purpose, and make the people around you better. That’s how your work will shape the journey of tens of thousands of partners — and the millions of customers they serve.

3 signs this job is(n’t) for you

Yes

- Learn and develop

You’re excited to grow your skills in analytics, product thinking, and modern software development — and you thrive in a fast-paced, learning-focused environment.

-Moving forward

You draw energy from experimenting, problem-solving, and writing SQL and Python that actually drive impact.
- Sharing is caring

You actively share knowledge, challenge your team, and believe continuous improvement applies to people and processes alike.

No

- Wallflower

You're hesitant to voice your opinion or tend to fade into the background during discussions.
- One trick pony

Your job ends at delivering the analysis, and you don't care what happens next.
- Old school

You're stuck in your ways and distrust new methods — experimentation, iteration, and learning are how we roll.