• Data cleaning & preparation: Clean, recode, and structure incoming survey datasets - including applying advanced data quality checks and filters, raking & weighing, missing data, etc. • Conduct foundational data exploration including frequency distributions, cross-tabulations, and basic descriptive analyses, primarily in SPSS • Work fluently across survey data formats, principally SPSS (.sav) and R-native formats • Conduct advanced cluster analysis on complex, multi-country survey datasets, working hand in hand with the Head of Data & Research Methods regarding analytical decisions and final segmentation outputs • Evaluate and compare clustering approaches (e.g. k-means, hierarchical, latent class analysis, and others as appropriate) with a view to producing segments that are statistically robust, meaningful, and cross-nationally comparable • Manage the specific methodological challenges of complex survey data: dealing with varying variable types (nominal, ordinal, continuous), handling of translated or culturally non-equivalent items • Iteratively test and refine cluster solutions, systematically varying parameters and documenting the impact of each decision on outputs • Using existing, labelled segmentation outputs as a training base, design and fit (machine learning / train-test) an appropriate classification model to enable assignment of new respondents to established segments • Evaluate candidate classification approaches (e.g. random forest, logistic regression, LDA, gradient boosting, or others) and select the most appropriate given the data structure, segment separability, and intended use • Assess model performance rigorously using appropriate validation strategies (e.g. cross-validation, held-out test sets, confusion matrices, precision/recall) • Identify the minimum set of survey questions ('golden questions') that are most predictive of segment membership — i.e. those that would need to be included in future quantitative research instruments to allow reliable classification of new respondents • Apply appropriate variable importance and feature selection techniques to identify and rank candidate questions, and validate their predictive power • Produce clear recommendations on the golden question set, including supporting evidence and sensitivity analyses • Design and implement a practical classification tool or calculator that can be applied to future survey datasets to assign respondents to segments based on the golden question set • Maintain detailed records of all analytical iterations, including variations in parameters, model specifications, and the rationale behind decisions taken

• Analytics Engineer in People Analytics will be responsible for transforming strategic people (HR) data into clear, reliable, and actionable insights, supporting decision-making across People, Culture, and Talent Management; • This professional will use data visualization with Tableau to create analytical and operational dashboards, ensuring semantic consistency, adherence to business rules, and data quality; • Model and deliver people analytics data in a reliable, scalable, and business-oriented way, enabling high-value analyses and dashboards for the People, Culture, and Leadership teams;

Role Description We are currently looking for a Data Analyst to help our teams make data-driven decisions. Your main mission will be to prepare reports, automate analytical processes, and complete ad-hoc tasks. If you enjoy working with data, are able to find patterns in it, and can turn numbers into a comprehensible story, this role is for you. - Preparing data using SQL for further visualisation. - Developing DAGs in Airflow (working with Python). - Visualising data and building reports in Tableau. - Preparing regular reports and executing ad-hoc queries for the Retention Department. - Optimising existing data collection and processing processes. Qualifications - At least 1.5-2 years of commercial experience as a Data/Business Analyst (preferred). - Strong SQL skills (ability to write complex queries using CTEs, window functions, and joins). - Good knowledge of Python (experience with pandas, understanding of functions, ability to write modular scripts). - Experience working with Tableau. - Strong sense of responsibility and proactivity. - Fast learner with high attention to detail. Benefits - A flexible schedule and remote format, or offices in Warsaw/Kyiv — you choose. - 24 paid vacation days, sick leave, and health insurance (UA-based, other locations in progress). - A supportive, friendly team where knowledge-sharing is part of the culture. - Coverage for professional events and learning. - Birthday greetings, team-building events, and a warm human connection beyond work. - Zero joules of energy to the aggressor state, its affiliated businesses, or partners. Company Description We are a young, ambitious, and fast-growing company that creates innovative digital products and is confidently expanding its presence in global markets.

• Write detailed user stories and acceptance criteria by breaking down Epics for integration and reporting use cases. • Lead feature / data product kickoffs to ensure business context and delivery alignment. • Facilitate estimation sessions and story readiness to support sprint planning. • Collaborate closely with developers and testers to validate “done” stories and ensure Client sign-off. • Partner with technical leads, client SMEs to ensure requirements are accurate, complete, and technically feasible. • Support the Client in managing and prioritizing the product backlog to ensure alignment with business goals. • Conduct backlog refinement sessions with the team to clarify requirements, dependencies, and priorities. • Ensure stories meet the teamʼs definition of ready before sprint planning. • Track and communicate backlog health and sprint progress through Agile tools (e.g., Jira). • Identify and escalate risks or blockers impacting backlog items or delivery flow. • Maintain visibility of dependencies and ensure alignment between epics, features, and stories. • Act as the liaison between client stakeholders and delivery teams, ensuring clear communication of needs and priorities. • Support stakeholder alignment and facilitate sign-offs at key delivery stages. • Work collaboratively with Account Managers, Program and Project Managers, Tech Leads, Developers and Testers to address client pain points and deliver outcomes. • Support data product to data source mapping activities and maintain alignment with the data catalogue. • Create and review target-to-source field mappings for individual data products. • Understand and articulate data reconciliation, data quality (DQ), and transformation rules within the medallion architecture for individual data products. • Facilitate Agile ceremonies, including daily stand-ups, backlog refinement, sprint planning, retrospectives, and show & tell sessions. • Support story validation and sign-off activities during sprints. • Maintain and communicate delivery roadmaps on Jira or similar tools. • Contribute to continuous improvement discussions and team retrospectives to enhance delivery health. • Track and report team health metrics through retrospectives and delivery KPIs. • Produce end-of-sprint reports summarizing story progress, carried-over items, and upcoming priorities. • Collaborate with account and delivery leadership (PO, Program/Project Manager, Account Manager, Tech Lead) as part of the Account Leadership Team (CAT). • Provide analytical insights into client pain points and support identification of improvement or growth opportunities.