The Senior HR Analyst turns people data into clear insights that support business and leadership decisions. This role builds predictive models, improves data quality and pipelines, and proactively identifies risks and opportunities, while working closely with stakeholders to connect HR data with business goals.

Key Responsibilities:

• Strategic Insights & ROI: Translate soft HR metrics into financial ROI models and profitability analysis to influence executive decision-making.
• Predictive Modeling: Build sophisticated models to forecast long-term costs, attrition risks, and talent supply scenarios to guide planning.
• Improvement Opportunities: Proactively identify strategic organizational risks and profit-generating opportunities before stakeholders ask for them.
• Data Pipelines: Architect the long-term data warehouse strategy and set technical standards for code quality and engineering best practices.
• Data Quality: Establish data privacy frameworks and role-based access controls to ensure compliance with global regulations, while overseeing more junior team members’ approaches and results
• AI Strategy: Lead the strategy for AI adoption in PnC, defining how custom agents and advanced engineering techniques drive team throughput.
• Stakeholder Management: Act as a bridge between technical data and business goals, translating operational needs into actionable insights for mid-level management.

Skills, Knowledge & Expertis:

• Bachelor’s degree in a quantitative field (e.g. Statistics, Mathematics, Economics, Computer Science); Sociology, Data Science, or People Analytics is a plus.
• Proven experience of 4+ years in those fields can substitute the education options (even self-taught with a strong portfolio can be considered).
• B2 or above (all analysis and reports, and most of stakeholder management will be in English)
• Know all HR functions and data they generate (or can generate)
• Statistics: distributions, central tendencies, variance, proportions, hypothesis testing, correlation, regression, data visualization concepts
• Data engineering: data types, databases, data warehousing concepts
• Project Management: general approach, project cycle steps, frameworks
• Presentation: make great presentations (both slides and delivery)
• Data Analysis: use data to produce actionable insights (incl.EDA, hypothesis tests, outliers, models)
• Data Visualization: use charts and dashboards to influence and tell stories
• Data Architechture: ensure data integrity, cleanup, use DWH
• AI: know up-to-date tools and trends, use to optimize workflows
• Stakeholder management: identify stakeholders, collect inputs, manage expectations
• Communication: build connections with colleagues, super respectful to build positive collaboration
• Developist mindset: seek solutions instead of excuses, stay curious, treat problems as opportunities

Job Benefits:

• Stable salary, official employment
• Health insurance
• Hybrid work mode and flexile schedule
• Relocation package offered for candidates from other regions
• Access to professional counseling services including psychological, financial, and legal support
• Discount club membership
• Diverse internal training programs
• Partially or fully payed additional training courses
• All necessary work equipment