Top Data Analyst Jobs in Amsterdam

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.

The Data Analyst will build and maintain dbt models, analyze billing and SaaS metrics, monitor data quality, maintain Metabase reporting, and support acquisition due diligence. The role involves tracing data from source systems through ingestion and transformation, resolving production issues, validating results, and communicating findings to technical and business stakeholders. The analyst will also maintain Airbyte integrations, document data definitions, and use AI tools responsibly in daily data work.

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.

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.

Lead complex analytics projects, translate business questions into data-driven recommendations, and advise senior stakeholders on strategy and decision-making. Develop analyses, metrics, and reporting solutions while managing multiple priorities and collaborating cross-functionally. Serve as a subject matter expert, evaluate emerging analytics tools including AI-assisted techniques, and coach junior analysts.

Leads complex analytics projects, translating business questions into actionable insights and recommendations. Partners with senior stakeholders, develops metrics and reporting solutions, manages multiple priorities, collaborates cross-functionally, evaluates emerging analytics tools including AI-assisted techniques, and mentors junior analysts.

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.

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.

Lead marketing analytics and M&A data integration initiatives. Harmonize KPIs, attribution, reporting, and data landscapes; build scalable marketing data models and ELT pipelines; create dashboards; analyze advertising and mobile measurement platforms; deliver executive insights; and lead cross-functional analytics projects involving multiple business units.

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.

Perform data analysis across growth revenue management, marketing, customer lifecycle, CRM, and risk analytics. Use statistical and programming tools to acquire, clean, integrate, analyze, interpret, and visualize data. Develop hypotheses and actionable recommendations, present findings, facilitate workshops, manage executive stakeholders, and mentor team members.

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.

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.

Analyze and instrument offsite discovery and SEO/GEO performance for ecommerce sites. Build integrations, ETL pipelines, and models to track organic and AI-driven traffic. Create tooling and frameworks for technical site audits, landing page modelling, SEO experiments, and enablement for product and customer teams.

Own supply-side analytics: define and monitor partner KPIs, build self-serve dashboards and LLM-powered tools, run experiments and A/B tests, create business cases for commercial decisions, support provider integrations, and raise analytics standards across the team.

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.