Top Data Analyst Jobs in Krakow

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.

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.

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 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.

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.

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 payment data to explain performance changes, identify trends and anomalies, and support Product, Risk, Finance, and Sales decisions. Prepare and validate datasets, apply statistical methods, build Superset dashboards and Druid cubes, deliver regulatory and stakeholder reporting, and automate recurring analysis. The role also requires presenting actionable insights, translating business questions into analytical work, and collaborating across departments.

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.

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.

Supports finance analytics by extracting and preparing data with SQL, maintaining reporting and reconciliation scripts, checking data quality, and explaining findings. Builds dashboards and data marts, researches unit economics and plan-versus-actual performance, and collaborates with finance, commercial, marketing, and product stakeholders. The role requires BI tools, Excel, business metrics knowledge, and strong analytical communication.

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.

Develop and support analytical systems for operational decision-making, identify KPIs with business process owners, analyze data lifecycles, define data warehouse and ETL requirements, validate data engineering results, build dashboards, and present insights to customers. The role requires at least one year of data or BI analyst experience, strong SQL and data visualization skills, analytical communication abilities, and fluency in Russian and English.

Analyzes clinical and operational data to support risk-based quality management and data surveillance. Develops surveillance plans, configures monitoring technologies, evaluates trends and outliers, identifies data quality issues, documents findings, and supports project reviews, meetings, audits, and regulatory inspections. The role requires programming in SAS, R, or SQL, data analysis expertise, familiarity with centralized monitoring and SDTM, and strong communication skills.

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.

Collect, clean, and analyze procurement data to drive sourcing strategies, supplier performance, and process improvements. Build and maintain Power BI dashboards and reports, lead data cleansing and classification, support sourcing events (RFx), execute MRP processes in SAP APO/ECC, prepare forecasts, and collaborate with cross-regional procurement and category teams to align POs and resolve supply issues.

The Data Analyst will assist with visa/VOE case history, data entry for new hires, and resolve employee queries using HRMS while ensuring quality and 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.

Analyze marketing data to evaluate spend, build attribution and reporting, and deliver actionable insights. Create and maintain dashboards, ensure data integrity, collaborate with marketing and data engineering teams, and improve analytical methods to support data-driven decisions.