Top Data Analyst Jobs in Hamburg

Analyze FMCG sales, pricing, promotions, customer, product, margin, market share, and competitor data to support revenue growth management. Develop pricing and price elasticity models, identify commercial opportunities, create visualizations and actionable insights, and translate analytical needs into product requirements, user stories, and business rules. Collaborate with stakeholders, product managers, data engineers, developers, and commercial teams to build scalable digital analytics solutions.

Analyze and improve fraud signals and user segmentation for Puzzleplay’s rewards platform. Investigate suspicious and manually reviewed users, monitor segment effectiveness, identify gaps in detection, and recommend verification tools. Collaborate with product and data teams to turn analysis into operational fraud controls across different markets as fraud patterns evolve.

Own GTM and sales analytics across pipeline performance, forecasting, funnel conversion, win/loss analysis, lead and account scoring, territory planning, quota modeling, and capacity planning. Partner with RevOps, Sales, Product, Finance, and Analytics Engineering to improve metric definitions, Salesforce and product data models, dashboards, and decision-making. Translate complex analysis into clear recommendations for GTM leadership.

Support client projects by structuring business problems, assessing data, selecting analytical approaches, conducting analyses, building and validating models, and translating findings into recommendations. The role involves quantitative consulting across industries, collaboration with clients and project teams, and potential work in AI, credit risk, sustainability, optimization, GenAI, and supply chain analytics. Business fluency in German and English and willingness to travel are required.

Supports client projects by structuring analytical problems, assessing data, selecting analytical methods, conducting analyses, building and validating models, and translating results into recommendations. Work may involve AI, predictive modeling, portfolio decarbonization, credit risk, optimization, chatbots, and supply-chain analytics. The role also includes client collaboration, communicating complex concepts clearly, and contributing to project teams across industries.

Perform deep operational data analysis, build queries and dashboards, automate ETL and data processes, develop monitoring tools, present insights and recommendations to management, and collaborate with squads using SQL, Python/R and visualization tools.

Analyze large datasets to identify trends and deliver actionable insights; design and monitor KPIs; build and maintain dashboards and reporting frameworks; conduct ad hoc analyses; ensure data quality and support reporting infrastructure in partnership with product and business teams.

Early-career Data Analyst responsible for designing and owning core metrics and dashboards, analyzing transaction/customer/credit data to inform credit, fraud, AML, portfolio and growth decisions, building data pipelines and automations with SQL and Python, partnering with cross-functional teams, and owning compliance reporting. Emphasis on turning ambiguous problems into reliable analytical systems and applying GenAI/LLMs for practical automation.

Partner with founders and cross-functional teams to analyze financial and operational data, build executive dashboards, create P&L and margin analyses, forecast and model unit economics, identify cost leaks, reconcile transactions, and present recommendations to improve profitability, cash flow, and business performance.

Partner with Marketing, Sales, Finance, Product and other teams to turn business questions into actionable analysis. Own end-to-end analytics: build datasets and dashboards (dbt, LookML), maintain metric definitions and caveats, use and curate agent tooling for trustworthy answers, and contribute small data platform and pipeline improvements.

Lead cross-functional analytics to drive commercial, marketing, and financial decisions. Monitor performance, model impact, build dashboards and automate reporting, ensure data integrity, and translate ambiguous business questions into decision-ready insights that shape profitability and resource allocation.

Lead technical analyses to detect and prevent ad fraud at scale. Build and optimize SQL/Python data pipelines, apply anomaly detection methods, design experiments, automate reusable analytics frameworks, and communicate findings to technical and non-technical stakeholders to drive business decisions.

Lead experimentation and A/B testing analyses using SQL and Python on large-scale data (100TB). Design experiments, compute sample sizes, apply variance reduction, detect anomalies, automate reporting and dashboards, and collaborate with product, engineering, and growth teams to translate results into business decisions.

As a Senior Data Analyst in Operations, you'll analyze data to provide insights that drive business decisions, enhance performance, and support strategic initiatives.