Top Data Analyst Jobs in Warsaw

Own A/B testing and analysis for Paper.io 2, using large datasets to uncover player behavior and growth opportunities. Translate insights into game design and product roadmap recommendations, optimize monetization and core KPIs, and build dashboards and reports. Collaborate with designers, product managers, and developers in a fast-paced live-ops environment.

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.

Analyze payments data, integrate complex data sources, maintain performance reports, monitor KPIs, and identify opportunities to optimize payment routing and reduce failures and costs. The role collaborates with Payment Operations, Product, Finance, Customer Support, analysts, and engineers to ensure data quality and deliver actionable insights through ad hoc analysis, dashboards, and automated reporting.

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.

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.

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.

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.

Build and support batch and streaming data pipelines, curated datasets, and Lakehouse platform capabilities. Responsibilities include data modeling, transformation, optimization, quality validation, reconciliation, testing, monitoring, and production support. The role partners with engineers and data consumers to deliver reliable data products for analytics, operational decision-making, and AI use cases.

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.

Leads data quality and governance for AML transaction monitoring, including access management, information security verification, records management, data lifecycle controls, and regulatory compliance. The role remediates data issues, oversees access entitlements across AML applications, validates critical data elements and PII, manages records deletion, advises management, and coordinates regulatory initiatives. It requires substantial AML, data management, records management, information security, and financial-services compliance expertise.

Processes, cleans, transforms, validates, and monitors data workflows to ensure accurate, timely client delivery. Investigates data inconsistencies and quality issues, maintains data integrity standards, documents workflows, collaborates with cross-functional teams, and supports process improvements that increase operational efficiency and scalability.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Ensures accurate, reliable, and timely delivery of client data by cleaning, transforming, validating, and monitoring data workflows. Investigates and resolves data quality issues, maintains data integrity standards, documents processes, and collaborates with cross-functional teams. The role also supports process improvement, operational efficiency, scalability, and effective management of multiple workflows and deadlines.

Coordinate the functional delivery of a Databricks HR data product that combines Mirakl WiFi, Zoom room booking, and Workday data. Align business, HR, data ownership, privacy, architecture, and engineering stakeholders to define scope, ensure reliability, document the solution, and maintain compliance with data protection requirements.

Owns functional and delivery coordination for data platform initiatives, translating business needs into requirements, user stories, and acceptance criteria. Coordinates stakeholders and engineering teams through discovery, development, validation, acceptance, and handover. Investigates data structures, sources, transformations, business rules, and quality issues using SQL or equivalent tools. Maintains documentation in Confluence and supports reporting and analytics teams with clear data definitions and context.