Top Data Analyst Jobs in Czechia

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.

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.

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.

Conduct primary and secondary research on the EMEA printing market, interview vendors and channel partners, analyze large datasets, identify trends and competitive dynamics, and produce market intelligence and forecasts. The role involves applying IDC methodologies and software, delivering research on schedule, presenting findings, and collaborating with geographically distributed teams while maintaining stakeholder relationships.

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.

Conduct exploratory and business data analysis, build and maintain dashboards, translate stakeholder needs into data work, support experiments and investigations, and document queries and standards. Present actionable findings clearly to nontechnical colleagues while ensuring data accuracy and reliability. The role includes working with SQL and data visualization, with opportunities to use Metabase, dbt, Python, or R.

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.

The Data Analyst will work with Business Teams to gather needs, analyze business performance, create reports and dashboards using Power BI, and conduct statistical analyses with R or Python.

Own and evolve data products supporting pharmaceutical Development Sciences and Clinical Supply. Gather requirements, define business rules, create logical data models, mappings, schemas, metadata, and lineage, and support data lifecycle management. Analyze laboratory and scientific data from LIMS, Signals, and related platforms while collaborating with scientists, engineers, architects, QA, and product teams. Support Agile delivery, UAT, documentation, data quality, governance, and GxP compliance.

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.

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.

Join an agile team delivering data management and transformation projects for leading banks. Analyze large datasets, define requirements, perform data mapping and data quality management, modernize processes, and support implementation. Gradually take ownership of topics and lead smaller sub-projects.

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.

Translates business needs into technical data requirements, mappings, transformation logic, acceptance criteria, and data quality rules. Partners with data engineers, product managers, architects, and governance teams on Databricks pipelines, dbt models, data contracts, lineage, and semantic data zones. Reviews and validates pipeline outputs, supports troubleshooting of job and test failures, documents data flows, contributes to agile backlog refinement, and promotes metadata completeness, governance, correctness, and traceability.

Analyze and improve multilingual text data quality by developing parsers, evaluating classifiers, translating taxonomies (Skills, Titles, Occupations), cleaning data in Excel, and applying language and text-analysis expertise in collaboration with Linguistics and Engineering teams.

Support multilingual data quality by analyzing and cleaning text data, developing parsers, evaluating text classifiers, translating taxonomies (Skills, Titles, Occupations), and partnering with Linguistics and Engineering to deliver high-quality global data.

Supports the design, deployment, validation, and operational management of laboratory instrument data acquisition platforms in pharmaceutical R&D environments. Configures hybrid on-premises and AWS infrastructure, troubleshoots instrument and software connectivity, manages releases, creates IQ/OQ and SDLC documentation, supports UAT, and coordinates global deployments. The role also provides technical support, user training, stakeholder communication, and leadership for small technical teams while ensuring GxP compliance.

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.

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.