Senior Data Analyst: Multiple Teams

This position is listed on behalf of a partner company, who manages all applications and next steps.

• Our partner is looking for a
• Senior
• Data

Analyst: Multiple Teams based in Germany.

You will work at the intersection of data, product, and machine learning, helping teams turn complex datasets into actionable business and product insights.

Your analysis will support a range of teams working across data science, ranking, recommendations, personalization, AI-powered shopping, search optimization, and retail media.

You will investigate user behavior, identify opportunities, and evaluate how product changes affect both customer experience and business performance.

A key part of the role will be designing experiments, defining meaningful metrics, and using statistical analysis to guide product decisions.

You will work with large-scale datasets using SQL and Python while building dashboards and analytical tools that make data accessible to decision-makers.

The role offers broad exposure to engineers, data scientists, product managers, customers, and business stakeholders.

You will join a collaborative, fast-moving environment where analytical thinking, ownership, clear communication, and measurable impact are highly valued.

• Accountabilities
• Analyze user behavior and large-scale datasets to uncover patterns, identify issues, and surface opportunities for product and business improvement.
• Design, run, and analyze A/B tests to evaluate product changes and quantify their impact on key business metrics.
• Define, validate, and monitor metrics that capture both user experience and business outcomes.
• Build dashboards, reports, analytical tools, and other data resources that support informed decision-making across multiple teams.
• Partner with engineers, data scientists, product managers, customers, and business stakeholders to translate analytical findings into actionable product improvements.
• Investigate product funnels, performance trends, and user behavior to identify opportunities for optimization.
• Apply SQL, Python, and distributed data systems to process, explore, and analyze large volumes of data.
• Contribute analytical expertise across different domains, which may include data science integrations, ranking, recommendations, AI shopping agents, search optimization, personalization, and retail media.
• Help teams understand machine learning-related data, including training data quality, model evaluation, and relevant performance metrics.
• Communicate findings and recommendations clearly, adapting the level of technical detail to different audiences and stakeholders.
• Take ownership of analytical projects from problem definition and investigation through to recommendations and measurable outcomes.

Requirements

• Strong analytical and problem-solving skills, with demonstrated experience using data to address business and product questions.
• Solid knowledge of SQL and experience working with large-scale datasets.
• Professional experience using Python for data analysis, including tools such as pandas, Num Py, and data visualization libraries.
• Good understanding of A/B testing, experimentation methodologies, and core statistical concepts.
• Experience defining and analyzing product metrics, metric trees, funnels, and other frameworks for measuring product performance.
• Understanding of machine learning pipelines, training data quality, and model evaluation.
• Familiarity with search relevance, ranking, or recommendation systems is a plus.
• Ability to translate ambiguous business questions into structured analytical approaches and actionable recommendations.
• Strong communication skills, with the ability to explain complex insights clearly to technical and non-technical stakeholders.
• Comfortable collaborating with multiple stakeholders in a fast-paced, cross-functional environment.
• Ability to work autonomously, take ownership of projects, and proactively identify opportunities to improve products and processes.
• Experience in a customer-facing role is a plus.
• Previous experience in e-commerce or product analytics is a plus.

Benefits

• Fully remote working environment, giving you flexibility over where you live and work.
• Unlimited vacation time, with employees strongly encouraged to take at least 3 weeks per year.
• Work-from-home stipend to help you create an effective home-office setup.
• Apple laptop provided for new employees.
• Annual training and professional development budget.
• Maternity and paternity leave for eligible employees.
• Opportunity to work with talented and empathetic colleagues while contributing to meaningful, high-impact projects.
• Regular team offsite events to connect and collaborate.
• Base salary of

$80,000–$120,000 USD , depending on knowledge, skills, experience, and interview results.

• Stock options offered in addition to the base salary.

How Jobgether works

We use an

AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements.

Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company.

The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice

By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer.

This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR).

You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information.

These tools assist our recruitment team but do not replace human judgment.

Final hiring decisions are ultimately made by humans.

If you would like more information about how your data is processed, please contact us.