Top Data Analyst Jobs in Poland

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.

Collects, maintains, researches, and quality-checks corporate actions data across financial markets. Responsibilities include database updates, completeness analysis, source review, process automation, release testing, report maintenance, monitoring market events, resolving client queries, and supporting continuous improvement. The role requires accurate, timely processing, financial market knowledge, collaboration, and mentoring junior team members.

Analyze and transform R&D master data using Python, PySpark, and SQL; identify data-quality issues; and build Power BI dashboards with advanced DAX models. Support AI/ML initiatives through feature engineering, training datasets, and predictive algorithms. Translate stakeholder needs into actionable BI features while ensuring compliance with data governance and GxP documentation standards.

Analyze and manage funds-related financial content within LSEG’s data environment. The role involves learning investment funds, asset classes, risk concepts, AI and emerging technologies, while identifying opportunities to optimize workflows using tools such as MS Fabric, Power Automate, and Power Apps. Previous experience is not required; curiosity, technical aptitude, continuous learning, and a growth mindset are emphasized.

The Data Analyst will build and maintain dbt models, analyze billing and SaaS metrics, monitor data quality, maintain Metabase reporting, and support acquisition due diligence. The role involves tracing data from source systems through ingestion and transformation, resolving production issues, validating results, and communicating findings to technical and business stakeholders. The analyst will also maintain Airbyte integrations, document data definitions, and use AI tools responsibly in daily data work.

Build sustainability dashboards, data models, templates, and reporting frameworks using Power BI, Excel, Snowflake, and Streamlit. Track ESG metrics including Scope 1–3 emissions, circularity, waste, water, energy, and materials. Establish data validation, governance, transformation, and audit-ready processes while partnering with IT and cross-functional teams. Conduct trend analysis, scenario modeling, and ad hoc analytics to support sustainability strategy and decision-making.

Develop and maintain Power BI dashboards and operational risk reports, prepare Risk Committee materials, analyze incidents and emerging risk patterns, monitor KRIs and KCIs, and improve risk data quality and governance. Support eFront UAT and business operations, maintain risk appetite reporting, and contribute to analytics transformation initiatives involving AI and advanced analytics. Collaborate with international risk managers and stakeholders across the organization.

Analyze large datasets and fraudulent patterns, prepare statistical reports, and write fraud detection rules to protect banking clients. The role involves SQL query development and optimization, programming, cybercrime analysis, business-rule reporting, automation, client support, and collaboration with analysts, developers, and alert-handling teams. Familiarity with Power BI, Python, VBA, HTML, JavaScript, Agile, and fraud detection systems is advantageous.

Perform daily investment data controls, reconciliations, data-quality reviews, and audit support using Clearwater and Excel. Collaborate with internal and external stakeholders, database providers, and auditors while supporting finance and data projects. The role requires strong analytical skills, attention to detail, investment interest, and availability three to four days per week during a six-month paid internship.

Supports IRC Poland’s MEAL and Programmes teams by integrating CommCare, KoboToolbox, and other data systems through OpenFn, APIs, and ETL processes. Builds and maintains CommCare-to-Excel connections, dashboards, datasets, and recurring reports. Monitors data flows, troubleshoots synchronization issues, documents integrations, and translates complex data into clear findings for technical and non-technical stakeholders.

The Commercial AI Solutions Analyst will collaborate with teams to implement AI initiatives and ensure data quality for business insights. Responsibilities include data validation, user acceptance testing, and promoting AI literacy within sales.

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.

Analyze product and business metrics, user behavior, retention, conversion, revenue, and lifecycle performance. Use SQL and BI tools to prepare data, build dashboards, investigate anomalies, monitor data quality, and identify root causes. Provide ad hoc analyses and actionable recommendations to product and leadership teams while documenting metrics and findings.

Analyze website traffic, conversion funnels, and digital campaign performance. Build automated dashboards in Looker Studio or Tableau. Write complex SQL to extract and blend data, manage GA4 tracking and BigQuery exports, generate insights tying web data to business outcomes, and support A/B test analysis for CRO.

Analyze high-volume battery telemetry data, build machine learning models for degradation, failure prediction, anomaly detection, and predictive maintenance, and develop AI-driven optimization strategies for energy storage operations. Create automated dashboards, perform root cause analysis on cell and module deviations, collaborate with engineering teams, and maintain documented, reproducible analytical pipelines.

Manage vendor and purchasing master data across procure-to-pay functions. Analyze large datasets, maintain data quality, resolve escalated issues, identify root causes, recommend corrective actions, and support compliant global processes. Create reports, dashboards, and KPI visibility while collaborating with purchasing, accounts payable, leadership, and other stakeholders. Contribute to process improvements, change management, workflow management, and operational excellence initiatives.

Manages customer account, security, and pricing reference data across multiple systems and teams. The role monitors data quality, identifies process improvements, supports client service, contributes to project delivery, supervises junior staff, and acts as backup for the manager. Responsibilities also include evaluating team performance, recommending improvements, and identifying training needs within a global financial services environment.

Maintains customer account, security, pricing, and reference data across multiple systems. Identifies data-quality and client-service improvements, supports risk and compliance controls, backs up the manager, guides team members, evaluates performance, and helps manage project initiatives and junior staff delivery.

Conducts data operations for client databases and reports by validating incoming data, coding products and characteristics, managing samples, monitoring file flows, and identifying data discrepancies. Maintains product catalogues, process documentation, statistical samples, and expansion factors. Investigates data inquiries, determines root causes, coordinates resolutions with local teams, and ensures product data accurately reflects market conditions.

Lead marketing analytics and M&A data integration initiatives. Harmonize KPIs, attribution, reporting, and data landscapes; build scalable marketing data models and ELT pipelines; create dashboards; analyze advertising and mobile measurement platforms; deliver executive insights; and lead cross-functional analytics projects involving multiple business units.

Lead business-facing data analysis to assess data models, identify duplicates and inconsistencies across sources, and recommend practical data quality and governance improvements. Run discovery sessions, present findings to stakeholders, produce documentation, roadmaps, and support prioritisation of data improvement initiatives to enable better business decisions.

Perform commercial data analysis and reporting across Western Europe, including distributor sales and price claims processing. Maintain the Commercial Excellence database, develop Excel-based tools, support Finance and commercial teams, provide local analytical support, and contribute to process-improvement projects. The role requires accurate data management, cross-functional collaboration, analytical recommendations, and communication in English and Polish.

Oversee the creation and maintenance of customer account, security, and pricing data across multiple systems. Identify data quality and client service improvements, support compliance and risk controls, provide team guidance, back up the manager, and supervise junior staff delivering project initiatives. Analyze inconsistencies, recommend policy and process improvements, assess risks, and ensure adherence to applicable regulations and company policies.

Build and maintain Tableau reports and dashboards, administer Tableau Server, and translate complex datasets into clear insights for non-technical stakeholders. Work with SQL and ETL pipelines to integrate and optimize large-scale data, troubleshoot performance, and support analytics team deliverables. Communicate findings, collaborate with peers, and continuously learn.

Maintain sales commission calculation and payment-support processes, calculate commissions for moderately complex plans, investigate commission claims, reconcile accounts, prepare reports, update sales compensation data and system configurations, communicate issues to stakeholders, and implement approved changes that improve data quality and operational efficiency.