Top Data Analyst Jobs in Amsterdam

Support Amazon EMEA business performance through dashboards, reporting, data analysis, forecasting, and actionable insights. The role analyzes retail and advertising data, supports business reviews, ensures data quality, automates recurring reports, and translates business questions into recommendations. Collaboration spans Sales, Marketing, Merchandising, and Supply Chain teams, with a focus on improving reporting tools, data models, and analytics capabilities.

Analyze and improve HR data quality across multiple countries in Workday. Investigate inconsistencies, identify root causes, define data standards, and propose actionable improvements. Build and support standardized HR reports, Power BI dashboards, and analyses for HR and business decision-making. Collaborate with HR stakeholders, the HR Business Process Owner, and technical teams to establish a reliable foundation for HR analytics.

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.

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.

Works with clients to solve business problems using data science, statistical modeling, machine learning, deep learning, generative AI, agentic AI, and NLP. Responsibilities include data cleansing, preprocessing, analysis, visualization, proof-of-concept development, stakeholder workshops, and deploying production-ready models on cloud platforms. The role translates technical insights into business recommendations and supports strategic outcomes.

Map new products using standardized specifications, origins, units, currencies, and frequencies. Check for duplicates and inconsistencies, identify data sources with the Data Research team, and hand mapped products to Product for implementation. Maintain accurate documentation throughout the project. The role requires structured, detail-oriented work, spreadsheet proficiency, clear English communication, and availability for 30–40 hours weekly for up to six months.

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.

The Finance & Data Analyst reconciles financial data across accounting, banking, and insurance carrier systems; writes SQL and Python for analysis and automation; builds dashboards and reporting tools; identifies anomalies and drives root-cause resolution; supports forecasting, budgeting, and cash-flow planning; and improves financial controls, data quality, and recurring finance workflows. The role partners with accounting, operations, engineers, and leadership in a multi-entity insurance scale-up.

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.

Senior Data Analyst partnering with product, commercial, and marketing teams to turn ambiguous business questions into actionable insights. Responsibilities include building KPI dashboards, analyzing large-scale datasets, measuring marketing impact and customer lifetime value, identifying conversion and monetization opportunities, and improving data quality and metric definitions. The role requires influencing stakeholders, communicating complex analyses, and working with SQL, Python, Databricks, and BI tools in a marketplace environment.

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.

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.

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.

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.

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.

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.

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.