Top Data Analyst Jobs in Czechia

Build and maintain datasets, dashboards, and reports analyzing customer usage, revenue, costs, forecasting, and budgeting. Reconcile source-system data with BI dashboards, investigate discrepancies, monitor metrics, support ad-hoc analysis, document processes, and help define shared semantic-layer metrics. The role uses SQL and BI tools across NetSuite, Salesforce, and Redshift, while supporting cloud cost, AI usage, customer profitability, renewals, and pricing analyses.

Analyze hotel supply data to support commercial and Cloud teams, evaluate partner and chain performance, identify inventory gaps and data-quality issues, and improve reporting consistency. The role involves clarifying ambiguous requests, delivering end-to-end analyses, building trusted dashboards or data products, and communicating findings to nontechnical stakeholders. Experience with SQL is required, while dbt, data modeling, and marketplace or platform experience are advantageous.

Build and maintain data pipelines for experimental, chemical, and biological data; integrate scientific data into a data lake; prepare datasets for AI/ML models; and enable visualization through LiveDesign, DataGrok, and Spotfire. Collaborate with scientific and technology teams to translate research questions into reliable data solutions supporting medicine and vaccine development.

Own analytics for Nuitee’s global travel marketplace, analyzing enterprise partners, self-service API adoption, bookings, product performance, and customer behavior. Build and validate dbt models, data pipelines, experimentation capabilities, and analytical products end to end. Partner with senior Product, Engineering, and commercial leaders to establish trusted metrics, resolve reporting inconsistencies, identify growth opportunities, and influence product and business decisions in a fast-moving startup environment.

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 cybersecurity risks, advise and control project security, support audits and compliance, and provide global data privacy support. Responsibilities include drafting and maintaining privacy documentation and databases, validating supplier security evidence, evaluating network and server architectures, interpreting penetration tests and vulnerability scans, and assessing access management and encryption controls.

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 regulatory analytics and reporting by building audit-ready datasets, pipelines, dashboards, compliance metrics, and automated workflows. Analyze complex data, monitor quality, support audits and regulatory exams, and deliver actionable insights to compliance teams and leadership. Translate regulatory requirements into accurate reports using Python, SQL, dbt, and Airflow while partnering cross-functionally to manage data issues and remediation.

Own end-to-end analytics for subscription products and web funnels, including KPI definition, dashboards, funnel and cohort analysis, payment performance, user behavior, experimentation, and anomaly monitoring. Build reliable SQL data models and maintain event taxonomies and tracking. Partner cross-functionally with Product, Marketing, Engineering, Finance, and BI to improve conversion, retention, revenue, and LTV. Mentor analysts and communicate actionable recommendations to stakeholders.

Leads a three-person data investigation team, spending approximately 80% of the time analyzing escalated customer data issues. Responsibilities include tracing metrics to source datasets, explaining findings, prioritizing investigations, improving team processes, creating documentation and dashboards, and partnering with analytics engineering to automate recurring questions through tools and AI-assisted products. Manages two direct reports while providing technical direction, reviewing engineering work, and communicating precisely with technical and nontechnical stakeholders.

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.

The Senior Data Analyst will support FP&A, Partnerships, and Product through ad hoc analysis, automated reporting, data transformations, visualization, and actionable insights. Responsibilities include managing the data lifecycle, identifying trends and opportunities, partnering with Data Engineering, and presenting findings to technical and business stakeholders. The role requires advanced SQL, Excel, Python, BI tools, modern data stack experience, finance technology and B2B SaaS expertise, and the ability to solve ambiguous problems independently.

Supports Development Sciences and Clinical Supply data products by gathering requirements, analyzing data from laboratory and manufacturing systems, documenting methodologies, and communicating findings. Collaborates with cross-functional and development teams, ensures regulatory compliance, and recommends product and operational improvements. Requires pharmaceutical domain knowledge, data analysis and visualization skills, cloud technology experience, and familiarity with Agile and product lifecycle management.

Analyze pricing, margins, discounts, profitability, customer behavior, and sales performance to identify commercial opportunities. Develop dashboards, reports, pricing simulations, and data-driven recommendations supporting pricing strategy, portfolio management, and sales efficiency. Collaborate with Sales, Product Management, Pricing, and Supply Chain teams while improving data quality and business processes. The role has global scope, requires occasional travel to France or Germany, and is based within commuting distance of Pardubice.

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, you will analyze data, optimize business processes, and support transformation projects for major banks. Collaboration in an agile team is key.

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.

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.

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.

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.

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

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.