Top Data Analyst Jobs in Prague

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.

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.

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.

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.

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

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.

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.

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.

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 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.

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.

Support Enterprise Risk Management through risk data collection, analysis, reporting automation, monitoring of key risk indicators, and management presentations. Develop and maintain Excel-based reporting processes and data transfer scripts, collaborate with stakeholders to validate business data, and identify reporting improvements. Assist with incident management, business continuity planning, and operational risk lessons learned. Translate complex risk topics into clear communications for varied audiences.

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.

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.

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.