Top Data Analyst Jobs in Poland

Business Analyst responsible for Market Risk data quality, end-to-end data lineage, process re-engineering, and AI/GenAI automation. The role analyzes data flows, change impacts, controls, and documentation while supporting FRTB and BCBS239 governance. Responsibilities include requirements gathering, process mapping, user stories, stakeholder management, and UAT coordination across Risk, Operations, Finance, and Technology teams.

Manages confidential-data access governance, including access requests, recertifications, removals, exceptions, stakeholder support, audit evidence, and data-quality checks. Uses SQL, Alteryx, Snowflake, and Excel for reconciliation and reporting. Partners with technology teams and data owners to resolve issues, maintain procedures, validate automated outputs, and improve controlled workflows while supporting audit readiness and risk management.

Develop and support enterprise Power BI solutions, including dashboards, reports, semantic data models, ETL processes, and governed datasets. Translate business requirements into scalable insights, apply dimensional modeling and DAX, optimize performance and refresh efficiency, ensure data quality, and standardize KPI reporting. Collaborate with data owners and global business partners while supporting secure, accurate, and actionable decision-making.

Collects and analyzes data across finance, operations, sales, marketing, and creative departments. Builds executive dashboards, reports, forecasts, business models, and cost-benefit analyses to support strategic decisions and revenue growth. Translates complex findings into clear presentations for technical and non-technical audiences, identifies optimization opportunities, supports client reporting, and provides recommendations to company leadership in a fully remote advertising-agency 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 large-scale audience datasets using Python and SQL to uncover streaming and media insights. Translate ambiguous questions into analytical problems, investigate data quality issues, create visualizations, and communicate findings to clients and internal teams. The role also supports client inquiries, cross-functional product improvements, and research accuracy initiatives.

Investigate and improve fraud signals, user segmentation, and review processes for a player rewards platform. Analyze suspicious activity, monitor segment performance, evaluate verification methods across markets, investigate manually flagged users, and recommend third-party fraud prevention tools. Collaborate with product, data, and gameplay analysts to translate findings into operational fraud controls and revenue-share decisions.

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.

Analyze large datasets covering customer behavior, marketing campaigns, and business performance. Build analytical datasets with SQL and PySpark, transform multi-source data, ensure data quality, and support segmentation, funnel, retention, churn, ROI, and campaign analysis. Collaborate with marketing analysts, stakeholders, and data teams to resolve data issues, improve workflows, optimize data models, and deliver ad hoc insights.

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 paid and organic marketing performance, allocate spend, build acquisition and conversion dashboards, investigate funnel and data issues, monitor attribution, and evaluate A/B experiments. The role provides data-driven recommendations to a cross-functional Demand and Supply team and requires strong SQL, Python, statistics, BI, communication, and marketing analytics skills.

Analyzes and validates HR data, creates reports, dashboards, and presentations, and translates findings into actionable recommendations. The role supports HR stakeholders and business leaders with data-driven insights, uses Excel and Power BI for visualization, and leverages AI to automate reporting and improve analytics processes. It also partners with HR teams to identify trends, solve business questions, and continuously improve reporting workflows.

Monitors and reports clinical study laboratory metrics, extracts and analyzes data, performs study risk assessments, and develops mitigation solutions. Creates customized monitoring packages and instructions, supports risk management plans, identifies data issues, and collaborates with developers and stakeholders to maintain study health, quality, compliance, and client satisfaction.

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.

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.

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.

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.

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.

Conduct clinical trial data risk assessments, identify data integrity issues, recommend mitigation strategies, and monitor data quality throughout trials. Collaborate with cross-functional teams on risk management plans, communicate statistical insights using analysis and visualization tools, and support regulatory documentation and audit preparation. The role requires clinical research or data analysis experience, strong analytical skills, English and Mandarin fluency, and knowledge of statistical and risk assessment methodologies.

Supports end-to-end healthcare and market data processing through ETL workflows, including file ingestion, Informatica PowerCenter execution, data validation, troubleshooting, reconciliation, and OD/BO loading. Monitors production workflows, investigates failures, performs root cause analysis, maintains operational documentation, supports period-close and business continuity activities, and communicates status and incidents to global stakeholders. The role also identifies automation and process-improvement opportunities.

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.

Develop and maintain data governance policies, standards, processes, and frameworks for a client account. Oversee master data management, data quality, metadata, data dictionaries, and stewardship programs. Collaborate with data consumers, producers, stewards, and business stakeholders to resolve data issues, facilitate governance decisions, and improve processes. Analyze data and communicate actionable recommendations using business-friendly presentations and reporting tools.