Top Data Analyst Jobs in Amsterdam

Analyze payments data, integrate complex data sources, maintain performance reports, monitor KPIs, and identify opportunities to optimize payment routing and reduce failures and costs. The role collaborates with Payment Operations, Product, Finance, Customer Support, analysts, and engineers to ensure data quality and deliver actionable insights through ad hoc analysis, dashboards, and automated reporting.

As a Data Analyst, you'll advise clients on data management strategies, implement solutions, and enhance data governance and quality. You'll also provide insights for business decisions based on analytical data evaluations.

Analyze hotel supply data to support commercial and Cloud teams, evaluate partner and chain performance, identify inventory gaps and data-quality issues, and improve reporting consistency. The role involves clarifying ambiguous requests, delivering end-to-end analyses, building trusted dashboards or data products, and communicating findings to nontechnical stakeholders. Experience with SQL is required, while dbt, data modeling, and marketplace or platform experience are advantageous.

Own analytics for Nuitee’s global travel marketplace, analyzing enterprise partners, self-service API adoption, bookings, product performance, and customer behavior. Build and validate dbt models, data pipelines, experimentation capabilities, and analytical products end to end. Partner with senior Product, Engineering, and commercial leaders to establish trusted metrics, resolve reporting inconsistencies, identify growth opportunities, and influence product and business decisions in a fast-moving startup environment.

Owns end-to-end product and commercial analytics for an AI cloud platform, including metric definition, customer health, capacity forecasting, utilization, pricing, packaging, segmentation, and monetization. Analyzes large-scale customer and usage datasets, builds production-ready data solutions, and delivers recommendations across Product, Engineering, Finance, Sales, and Operations. The role requires strong Python, SQL, statistics, commercial judgment, and familiarity with consumption-based technical products.

Maintains and improves client data quality by managing customer records, performing data entry, validation, reconciliation, reporting, and issue remediation. Supports CIF and account lifecycle activities, responds to front-office data queries, documents procedures, and escalates discrepancies. The role requires strong attention to detail, Excel skills, clear communication, and the ability to manage repetitive tasks and multiple priorities in a financial services environment.

Analyze large-scale user and product data, design and evaluate A/B tests, define and validate product and business metrics, build dashboards and reports, and partner with engineers, data scientists, product, and customers to translate insights into product improvements.

The job description provides company background but does not specify responsibilities, qualifications, technologies, compensation, location, travel, or clearance requirements for the Digital Product Data Analyst role.

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 complex analytics projects from business questions through delivery, developing reliable data products and solutions. Partner with product managers, analytics engineers, technologists, and senior stakeholders to shape data-driven strategy. Apply data preparation, blending, governance, and emerging AI techniques while coaching junior colleagues in analysis design, stakeholder engagement, and project management.

Own complex analytics projects from business questions through delivery, creating reliable data products and solutions. Partner with product managers, analytics engineers, technologists, and senior stakeholders to develop data models, semantic layers, and AI-enabled analytics. Apply governance, influence data-driven strategy, adopt emerging tools, and coach junior colleagues in analysis design, stakeholder engagement, and project management.

Drive enterprise data management and governance initiatives, gather and document requirements, support data quality, metadata, and master data management, and collaborate with business and technology teams on data solutions. The role requires stakeholder management, regulatory awareness, Agile delivery experience, and the ability to translate complex business needs into actionable data solutions.

Translates business requirements into ServiceNow data and ITSM solutions, advises stakeholders on OOTB capabilities, and supports platform strategy, roadmap, governance, and adoption. The role analyzes processes and data structures across CMDB, APM, CSDM, Platform Analytics, and ITOM; facilitates workshops; collaborates with architects and developers; and identifies improvement opportunities, risks, and opportunities from new ServiceNow capabilities.

Leads research and advisory work for CIOs on data, analytics, and AI strategy, governance, operating models, architecture, value realization, and emerging technologies. Develops thought leadership, market analysis, presentations, and actionable client guidance; evaluates agentic and composite AI, modern data platforms, AI-ready data, organizational maturity, and capability-building needs. Represents Gartner at client meetings and conferences, supports sales, mentors colleagues, and shapes research agendas.

Supports enterprise data governance implementation, including governance frameworks, policies, data ownership, metadata management, business glossaries, data catalogs, lineage, impact analysis, and data quality practices. Collaborates with business and technical stakeholders across Azure, Microsoft Fabric, Azure Databricks, data lakes, warehouses, and analytics platforms. Requires strong SQL, data architecture understanding, GDPR knowledge, and preferably Dutch P&C insurance experience.

The Digital Data Analyst ensures accurate data tracking, analyzes performance across digital channels, and reports insights to drive marketing decisions.

The FP&A Data Analyst will enhance financial reporting, automate processes, bridge data across systems, and develop insightful dashboards while collaborating with finance and engineering teams.

Supports Oliver Wyman’s Data and Analytics consulting team by designing analytical solutions, developing prototypes, applying machine learning and AI techniques, validating models, and assessing their effectiveness. The role involves collaborating with consultants and clients, explaining complex data science concepts clearly, and contributing to projects across financial services, sustainability, retail, transportation, and other industries. International travel and continuous technology development are expected.

Develop analytical solutions for consulting clients across financial services, sustainability, energy, retail, and transportation. Responsibilities include designing and prototyping data science solutions, applying machine learning and advanced analytics, validating models and GenAI applications, and communicating complex findings to clients and colleagues. The role involves collaboration across global teams, continuous learning, and potential international travel.

Collaborate with consultants and clients to design, prototype, validate, and implement data and analytics solutions. Projects may involve NLP, machine learning, GenAI validation, credit risk modeling, decarbonization, promotion optimization, supply chain risk, and customer churn. Explain sophisticated analytical concepts clearly, contribute to client discussions, and develop quantitative problem-solving skills in a collaborative consulting environment.

Develop analytical and machine learning solutions for global consulting clients, including prototypes, predictive models, NLP, GenAI validation, risk analytics, and optimization tools. Collaborate with clients and colleagues to explain sophisticated data science concepts, assess solution effectiveness, and deliver impactful results across industries such as financial services, energy, retail, and transportation.

Lead data extraction, validation, and migration efforts using advanced SQL and Azure data services. Perform data mapping, reconciliation, quality assessments, and root-cause analysis. Collaborate with stakeholders, data engineers, and project teams to translate requirements, support SIT/UAT, optimize SQL scripts, and maintain technical documentation to ensure data integrity and compliance across migration lifecycles.

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.