Top Data Analyst Jobs in Budapest

Leads ad hoc and exploratory analyses for medical and business questions across a global Medical Insights organization. Prepares and validates datasets, translates ambiguous stakeholder needs into decision-ready findings, and maintains analytical documentation. Tests new data sources, methods, and AI-enabled approaches through proof-of-concept analyses to guide platform investments and roadmap decisions. Partners with business and product stakeholders while supporting compliant, reproducible use of regulated data.

Performs procurement and supply chain data analysis, modeling, reporting, and visualization to identify cost savings, compliance, standardization, and process-improvement opportunities. Maintains and supports database systems, develops Power BI dashboards and scorecards, troubleshoots reports, and communicates statistical insights to stakeholders. Collaborates with business units, IT, senior analysts, and vendors on reporting, systems, training, and operational improvement projects.

As an Optimization Lead, you will maximize campaign performance using data-driven insights and collaborate with various teams to implement optimization strategies.

Ensures the quality, completeness, and accuracy of mortgage valuation data across reporting and valuation processes. Responsibilities include data validation, reconciliations, anomaly investigation, root cause analysis, output verification, stakeholder coordination, testing, documentation, audit controls, and process improvement. The role supports implementation of a new mortgage valuation platform and bridges Finance, Risk, Technology, data providers, and business teams.

Supports Citi’s enterprise cross-border data transfer clearance process and data transfer framework. Responsibilities include regulatory implementation, privacy and data governance assessments, target operating model development, process standardization, risk and control oversight, data analysis, reporting, and creation of playbooks and guidance. The role collaborates with legal, compliance, technology, and business teams across jurisdictions to ensure compliant execution and mitigate operational risks.

Lead analysis and visualization of complex datasets to support pricing, product, customer, market, supply chain, inventory, and operational decisions. Develop executive reporting, scalable data models, self-service analytics, and AI-enabled data quality capabilities. Investigate discrepancies, improve processes, define data requirements, and collaborate with global cross-functional teams. Translate complex insights for technical and non-technical audiences while mentoring junior analysts and driving continuous improvement.

This role involves analyzing employee engagement, culture, and DE&I metrics to provide actionable insights for HR leaders and stakeholders, using BI tools to create reports and dashboards, while ensuring adherence to data privacy standards.

Own marketing measurement and signal engineering across Meta, Google Ads, TikTok, and other ad platforms. Build and maintain server-to-server conversion pipelines, pixels, GTM releases, attribution conventions, marketing datasets, monitoring, alerts, and performance reports. Partner with Marketing, Product, Data Engineering, and ad platform representatives to improve signal quality, campaign optimization, and conversion tracking. The role requires advanced SQL, ad technology expertise, visualization skills, tracking knowledge, and clear communication with technical and nontechnical stakeholders.

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.

Develop and lead digital measurement strategies, analytics frameworks, dashboards, attribution models, funnel analysis, segmentation, and experimentation programs. Use Adobe Analytics, Power BI, Salesforce CRM Analytics, and integrated CRM and marketing data to generate executive-ready insights tied to pipeline and revenue. Establish tagging governance, data quality standards, tracking specifications, and self-service reporting. Partner cross-functionally with Web Strategy, Marketing, IT, Data, UX, and Product teams to improve digital engagement, conversion, customer experience, and commercial outcomes.

Design and implement enterprise-scale data pipelines, build governed Power BI datasets and dashboards, optimize cloud-based data workflows using Snowflake and Microsoft Fabric, apply data governance and performance optimization, and partner with finance and business stakeholders to drive analytics, automation and AI-enabled insights.

Analyzes clinical trial scientific and operational data to support risk-based quality management and centralized monitoring. Develops surveillance plans, configures KRIs and statistical analyses, reviews data for trends and outliers, documents findings, escalates quality issues, and collaborates with global project teams. Presents findings in internal and external meetings, supports regulatory inspections, coordinates follow-up actions, and completes central monitoring reports.

Design, build and maintain interactive BI dashboards, perform exploratory analysis on commodity markets, ensure data quality and pipelines, produce KPIs and insight reports, and support stakeholders with self-service analytics and training.

Develop and maintain the front-end of a risk and analytics platform using React (or similar), implement front-office features, design backend API endpoints, build data visualizations (Plotly, ApexChart, D3.js), code/test/debug/monitor functionality, and collaborate with cross-functional teams on technical requirements.

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 the billing analytics function: build and maintain billing data pipelines and dashboards, analyze payments/renewals/refunds/disputes, run experiments and forecasting, reduce churn and disputes, and manage/mentor a team of analysts while partnering with Billing, Support, Finance, Product, and Marketing.

Analyze billing and support performance, build and maintain data pipelines, apply statistical forecasting and A/B testing, collaborate cross-functionally, document analyses, and provide recommendations to reduce financial risk, disputes, churn, and operational inefficiencies.

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 Senior Data Analyst will conduct data analyses, support stakeholders with insights, design dashboards, and improve data quality to enhance user experiences and inform business strategies.

Serve as the data product owner and liaison between client stakeholders and delivery teams. Write and prioritise user stories, manage the backlog, facilitate Agile ceremonies, validate story completion, map data products to sources, ensure data quality and reconciliation within a medallion architecture, and report delivery metrics while supporting account growth.