Data Analyst - Process Mining

We are looking for a Data Analyst - Process Mining to join our team. In this position, you will be one of key drivers in transforming raw process data into actionable business insights, identifying inefficiencies, and providing data-driven recommendations. The primary focus is on optimizing process performance, uncovering improvement opportunities, and supporting operational excellence and business transformation through advanced analytical storytelling.

Data Analyst

Process Mining Requirements

• 3-5 years of experience as Data Analyst in financial services industry.
• Proficiency in Process Mining technologies (preferable Celonis),
• Hands-on PQL, SQL, Python, and various BI tools.
• Expertise in process mining techniques, including query and dashboard design.
• Advanced English language skills (C1 level).
• BSc degree in Management, IT, Project Management, Finance, or Business.

Responsibilities

• Analyze Process Mining data to identify inefficiencies, bottlenecks, and compliance deviations.
• Develop interactive dashboards and reports to provide visibility into key business metrics.
• Translate complex analytical findings into actionable recommendations for business transformation.
• Collaborate with stakeholders to define analytical requirements and validate process outcomes.
• Validate analytical data to ensure high levels of accuracy and reliability in all analyses.
• Measure process performance improvements to track the impact of optimization initiatives.

What We Offer

• Hybrid work mode, 50% working from home within a month
• Equivalent for remote work expenses (120 PLN per month)
• Stable employment in the international company
• Fully paid private medical care for employee
• Pre-paid lunch card
• Employee Pension Plan
• Co-financed Multisport Card
• MyBenefit Cafeteria Platform
• Life insurance
• Car parking availability in the office building
• Trainings and development opportunities

If the offer sounds interesting to you - please be invited to apply with your resume in English.