Data analyst - Customer Risk Lifecycle at N26

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• 🏢 N26 has 139 jobs here, 136 with visa sponsorship see all
• 🛂 Visa: EU Blue Card. Minimum salary: €50,700 a year guide
• 💡 No salary shown. Ask N26 if it is above the minimum.

Updated 2026-11-05, from our data and official sources.

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About the role

Responsibilities:
- Partner with the Customer Risk Lifecycle (CRL) and AFC Operations teams to enable data-driven decisions across product and operations.
- Define clear, measurable goals and improve forecasting and goal-setting processes for initiatives.
- Design, run and analyse experiments (A/B tests and observational studies); produce concise, actionable insights and recommendations.
- Build and maintain monitoring dashboards and weekly reporting to track impact against OKRs and KPIs.
- Improve analytics foundations and self-serve capabilities by working with engineers to ensure reliable data models and event tracking.
- Support product discovery and development by combining quantitative analysis with qualitative research to identify user friction and business opportunities.
- Educate and upskill teams through documentation, workshops and ad-hoc coaching to raise data literacy.
- Collaborate across the analytics community to share best practices, tools and reusable metrics.

Requirements:
- 3+ years experience in product analytics, data analytics or related roles.
- Strong SQL skills and practical experience in Python or R for data analysis.
- Experience with data visualization tools (Tableau, Looker, Metabase, Superset) and building dashboards for stakeholders.
- Solid understanding of statistical methods for experiments, A/B testing, and causal inference.
- Familiarity with tracking and instrumentation best practices to ensure event and metric quality.
- Strong communication and stakeholder management skills; able to translate analysis into clear business actions.
- Comfortable working cross-functionally in agile teams and driving initiatives end-to-end.
- Fintech, fraud or Anti-Financial Crime (AFC) experience is a strong plus.

Responsibilities

The Data Analyst will enable data-driven decision-making for the Customer Risk Lifecycle team by monitoring product initiatives and establishing a data-driven culture. Key tasks include developing measurable targets, building dashboards, and collaborating with cross-functional teams to optimize product performance.

Requirements

Candidates need 3+ years of experience in Product or Analytics with strong proficiency in SQL, Python/R, and data visualization tools. Experience in fintech, fraud, or AFC (Anti-Financial Crime) is considered a significant advantage.

Key skills

• SQL — in 545 other listings on The Stack
• Python — in 1200 other listings on The Stack
• R — in 45 other listings on The Stack
• Tableau — in 65 other listings on The Stack
• Metabase — in 22 other listings on The Stack
• Looker — in 44 other listings on The Stack
• Superset — in 18 other listings on The Stack
• Statistical Analysis — in 34 other listings on The Stack
• Data Visualization
• Quantitative Research
• Experimental Design
• Stakeholder Management
• Forecasting
• Product Analytics
• Data Literacy
• Communication Skills

On The Stack (as of 2026-11-05)

• N26 has 138 other listings on The Stack, 135 of them marked as offering visa sponsorship.
• 166 visa-sponsored jobs in Germany on The Stack, posted in the last 60 days.
• 24 visa-sponsored data analyst jobs in Europe on The Stack, posted in the last 60 days.

Frequently asked questions about N26

Is this Data analyst - Customer Risk Lifecycle role still open?

It was posted on 2026-07-03. Listings more than 30 days old may no longer be active, so check N26's site before applying.

Does N26 offer visa sponsorship?

This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on N26's site.

Where is this role located?

The listing gives the location as Germany. It is marked on-site.

What skills does this role ask for?

The listing names: SQL, Python, R, Tableau, Metabase, Looker, Superset, Statistical Analysis, Data Visualization, Quantitative Research, Experimental Design, Stakeholder Management, Forecasting, Product Analytics, Data Literacy, Communication Skills.