Top Data Analyst Jobs in Budapest

Build scalable data architectures, dashboards, ETL strategies, and AI-enabled analytical solutions using Salesforce data platforms. Analyze patterns, create forecasts and predictive models, and deliver actionable insights for business decision-making. Collaborate cross-functionally to align analytics solutions with business goals and architecture standards. The role requires experience with Salesforce data, Tableau or Power BI, statistics, Python, structured and unstructured data, predictive modeling, AI technologies, and Salesforce Service Cloud.

Develops and maintains forecasting models for clinical site payments, integrating Medidata Payments data and supporting financial reporting. Analyzes plan-versus-actual performance, budget variances, and forecast risks; prepares client-ready reports and reconciliations. Partners with Revenue Recognition, Clinical Operations, Project Analysis, and planning teams to support audits, change orders, study closeouts, compliance, and sponsor reporting requirements.

Monitors medical device complaint data flowing from Salesforce into Snowflake, maintains Power BI dashboards, performs SQL trend analyses, and presents signal detection findings to QA, regulatory, and operations teams. Ensures data quality, traceability, documentation, and alignment with post-market surveillance, complaint-handling, audit, and regulatory requirements.

Lead analytics for subscription products and web funnels, partnering with Product, Marketing, and Data teams to improve conversion, retention, and LTV. Build trusted dashboards, SQL data models, event tracking structures, funnel and cohort analyses, and A/B testing insights. Monitor metrics, identify anomalies, communicate recommendations, and mentor junior and mid-level analysts while maintaining reliable reporting and data foundations.

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.

Own end-to-end product and marketing analytics for subscription products and web funnels. Define KPIs, build trusted dashboards and reusable SQL data models, analyze funnels, cohorts, retention, LTV, churn, and user behavior, and identify optimization opportunities. Maintain event tracking and taxonomy, monitor anomalies, communicate insights to stakeholders, and mentor junior and mid-level analysts. Collaborate cross-functionally with Product, Marketing, Data Engineering, and BI teams to support experimentation and data-driven decisions.

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.

Design finance data models, requirements, mappings, standards, lineage, and scalable data solutions. Support migration to Snowflake, data quality and governance, regulatory reporting, automation, and AI-enabled analytics. Collaborate with Finance, Data, and Technology stakeholders to translate business needs into technical specifications and improve data accessibility, reliability, and usability.

The Senior Data Analyst will provide product, operations, and business analytics; analyze internal, market, and customer data; translate findings into actionable insights; improve product features; define data models; ensure data quality; and build dashboards and analytical models using Snowflake, Looker, Amplitude, and related tools. The role also involves A/B testing, causal inference, stakeholder communication, and collaboration with data engineers.

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.

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.

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.

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 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 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.

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.