Top Data Analyst Jobs in Prague

As a Data Analyst, you will work on transformation projects with large banks, focusing on data analysis, business process optimization, and agile method implementation.

As a Data Analyst at Similarweb, you'll manage data collection, validate data quality, automate processes using AI, and collaborate with teams to enhance data insights.

Design and implement AI projects, balance technical complexity with business impact, and collaborate with stakeholders to deliver value using AI and data.

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.

Work as a business/data analyst on banking transformation projects: analyze and validate large datasets, define data quality rules, perform as-is process and data analysis, write requirements and data mappings, support implementation, and progressively lead sub-projects and small teams.

Support monitoring, validation, and maintenance of spectroscopy-based authentication models (NIR mandatory). Interpret model performance, create model snapshots and metadata checks, collaborate with Data Scientists, contribute to validation and release, and document methods and changes for regulated environments.

Lead delivery of end-to-end data and analytics solutions: build dimensional models, develop Power BI dashboards, perform exploratory analysis, design Azure-based data pipelines, capture client requirements, run scenario modelling, test and assure solutions, prepare client communications and lead project teams.

Lead data and analytics projects: design dimensional models, build Power BI dashboards, run exploratory analysis, capture client requirements, develop end-to-end data pipelines on Azure, test and assure solutions, support client decision-making, and contribute to business generation and people development.

Gather business requirements, analyze and profile enterprise data, develop KPIs, reporting frameworks, and analytical models. Perform forecasting, scenario modeling, and statistical analysis, validate dashboards and reports, and collaborate with business and technical teams to support strategic workforce planning and decision-making.

Own end-to-end product analytics for the Pro team: build production-grade pipelines and dbt models, define north-star metrics, design A/B tests and causal inference frameworks, create dashboards and metric frameworks, embed AI tooling, and translate insights into product recommendations for leadership.

The Data Operations Analyst will manage data collection processes, perform quality assurance, monitor data accuracy, and enhance operational efficiency in data analytics.

Lead HR analytics and insights for global talent acquisition and onboarding. Build and maintain dashboards, KPI frameworks, and reports; analyze operational metrics; drive process improvement and change enablement; create stakeholder-facing resources and training; partner across HR, data, and technology teams to improve recruiting and onboarding performance and adoption.

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.

Lead insider risk and data loss investigations from triage to closure, operate and tune DLP across environments, build detections and workflows, partner with HR/Legal/Compliance/IT, mature insider risk program, support audits, and mentor others.

Manage and improve commercial master data for Emerging Markets Surgery: validate changes, coordinate bulk uploads, resolve data quality issues, enforce governance and controls, support CRM and commercial platforms, lead testing and release readiness, reconcile data for reporting and incentives, and drive process improvements and stakeholder communication.

As a Senior Data Analyst, you will analyze data, create reports, manage data pipelines, and provide insights to influence product decisions. You will collaborate with various teams and perform A/B testing.

The Senior Data Analyst will apply analytics to business problems, developing data products and collaborating with teams to deliver solutions while maintaining quality code.

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.

Maintain and validate global customer master data across systems (Salesforce, Jira), perform deduplication and hierarchy management, conduct compliance checks (embargo/VAT screening), monitor CMD dashboards, support cross-functional teams to resolve data anomalies, and drive data integrity projects and process improvements.

Use SQL and Python to analyse transaction monitoring and fraud rule performance, identify patterns and anomalies, reduce false positives, and prioritise high-risk cases. Partner with FinCrime, Product, Compliance and Data teams to improve controls, data pipelines and detection logic, support scoring and future ML use cases, and translate analysis into actionable recommendations that balance fraud prevention with customer friction.

Support a UK healthcare/pharmacy client in enterprise data strategy, governance and data quality. Coordinate data backlog, establish governance and ownership models, contribute to customer data strategy, and help define reporting and analytics operating models. Prepare analysis, documentation and recommendations for programme decision-making.