02/26/2025 updated
100 % available
Project Data Management | Data Migration & Quality | IT Business Solutions | AI Solution
Prague, Czech Republic
Worldwide
Master degree in EconomicsPythonMachine Learning (Python) • Blockchain • IoTSAP ConsultingSAP MM Project Data Migration Manager S4 HANABig Data ManagementData CleansingData qualityArtificial intelligence Natural language processingData GovernanceIT project managementCross functional integrationMasterdata
With over 17 years of experience leading Intelligent Process Automation (IPA) and data projects, I specialize in ERP systems and AI-driven solutions that enhance data quality and decision-making.
Core Skills and Experience:
• AI & Machine Learning: Skilled in implementing AI-driven models and leveraging machine learning to optimize data accuracy and predictive insights.
• Python & NLP Expertise: Experienced with Python for automation and data analysis, including NLP models for comparing financial and legal data.
• ERP & SAP S/4 HANA: Deep expertise in ERP systems and SAP S/4 HANA, with a focus on data governance, quality, and seamless data migrations.
• Data Governance & Automation: experience in SAP master data management, data quality improvements, and automation through advanced tools.
• Project Leadership: Strong history of coordinating data projects, collaborating with stakeholders, and managing cross-functional teams.
Notable Experience:
At Swiss Re, I managed data quality in asset management using Python for automated checks and reporting, where I applied advanced governance practices and AI-driven automation to strengthen data handling and operational efficiency. Previous roles with Google, Apple, and Eli Lilly expanded my expertise in SAP data governance and process automation to improve data reliability and efficiency.
Achievements:
• Developed effective AI-based data solutions that future-proof data operations.
• Strengthened data governance and compliance through machine learning.
• Built and coached successful ice hockey programs as a certified international skills coach.
Technical Skills:
• Programming: Python
• Tools & Methodologies: ERP, SAP S/4 HANA, Data Migration, Data Governance, Automation, Machine Learning, AI
• Data Management: Master Data, Metadata, Reference Data
Core Skills and Experience:
• AI & Machine Learning: Skilled in implementing AI-driven models and leveraging machine learning to optimize data accuracy and predictive insights.
• Python & NLP Expertise: Experienced with Python for automation and data analysis, including NLP models for comparing financial and legal data.
• ERP & SAP S/4 HANA: Deep expertise in ERP systems and SAP S/4 HANA, with a focus on data governance, quality, and seamless data migrations.
• Data Governance & Automation: experience in SAP master data management, data quality improvements, and automation through advanced tools.
• Project Leadership: Strong history of coordinating data projects, collaborating with stakeholders, and managing cross-functional teams.
Notable Experience:
At Swiss Re, I managed data quality in asset management using Python for automated checks and reporting, where I applied advanced governance practices and AI-driven automation to strengthen data handling and operational efficiency. Previous roles with Google, Apple, and Eli Lilly expanded my expertise in SAP data governance and process automation to improve data reliability and efficiency.
Achievements:
• Developed effective AI-based data solutions that future-proof data operations.
• Strengthened data governance and compliance through machine learning.
• Built and coached successful ice hockey programs as a certified international skills coach.
Technical Skills:
• Programming: Python
• Tools & Methodologies: ERP, SAP S/4 HANA, Data Migration, Data Governance, Automation, Machine Learning, AI
• Data Management: Master Data, Metadata, Reference Data
Languages
GermanGoodEnglishFluentCzechNative speaker
Project history
• Led Finance Data Governance in Group Finance, establishing robust frameworks that elevated data quality standards and governance policies across Legal Entity operations.
• Developed and deployed Python-based automation for data quality assurance in Asset Management, implemented AI algorithms to perform advanced checks and anomaly detection, reducing data discrepancies by 80%.
• Implemented AI-enhanced data management practices, establishing dynamic naming conventions, ownership protocols, and change management processes that improved data integrity and traceability.
• Drove data analytics initiatives, enabling strategic decision-making with insights that influenced finance and regulatory compliance processes.
• Collaborated with cross-functional teams to refine finance application architecture, spearheading data modeling and reconciliation efforts to ensure 99% alignment in regulatory and internal reporting.
• Developed and deployed Python-based automation for data quality assurance in Asset Management, implemented AI algorithms to perform advanced checks and anomaly detection, reducing data discrepancies by 80%.
• Implemented AI-enhanced data management practices, establishing dynamic naming conventions, ownership protocols, and change management processes that improved data integrity and traceability.
• Drove data analytics initiatives, enabling strategic decision-making with insights that influenced finance and regulatory compliance processes.
• Collaborated with cross-functional teams to refine finance application architecture, spearheading data modeling and reconciliation efforts to ensure 99% alignment in regulatory and internal reporting.
• Directed IAM Data Quality initiatives leveraging JIRA Atlassian, implementing metrics and workflows to boost data accuracy and integrity by 90%.
• Enhanced system and data security by managing user access protocols, securing enterprise resources and optimizing compliance with IAM best practices.
• Applied advanced analytics to collect, analyze, and interpret data quality metrics, employing algorithms to identify patterns, forecast trends, and provide actionable insights for risk mitigation.
• Innovated data collection methodologies and analytics processes, transformed models to continuously monitor and improve data quality across systems.
• Enhanced system and data security by managing user access protocols, securing enterprise resources and optimizing compliance with IAM best practices.
• Applied advanced analytics to collect, analyze, and interpret data quality metrics, employing algorithms to identify patterns, forecast trends, and provide actionable insights for risk mitigation.
• Innovated data collection methodologies and analytics processes, transformed models to continuously monitor and improve data quality across systems.
• Led efficient global implementation of business data systems, directing the S/4 HANA migration and providing strategic consulting to senior stakeholders, resulting in 30% faster adoption across regions.
• Coordinated cross-functional project teams to manage, establish, and finalize data management projects, ensuring seamless data integration and consistent handling across all stages.
• Drove strategic data management initiatives, focusing on data architecture, solution design, and end-to-end testing, with a core emphasis on SAP Master Data optimization.
• Developed and enforced comprehensive data governance standards and best practices for material master data, aligning data assets with regulatory and business requirements.
• Deployed Winshuttle Business System Process automation and advanced reporting analytics, enhancing Master Data process and decision-making capabilities.
• Directed data cleansing and quality improvement efforts, leveraging ERP systems to achieve high data accuracy and streamlined operations.
• Coordinated cross-functional project teams to manage, establish, and finalize data management projects, ensuring seamless data integration and consistent handling across all stages.
• Drove strategic data management initiatives, focusing on data architecture, solution design, and end-to-end testing, with a core emphasis on SAP Master Data optimization.
• Developed and enforced comprehensive data governance standards and best practices for material master data, aligning data assets with regulatory and business requirements.
• Deployed Winshuttle Business System Process automation and advanced reporting analytics, enhancing Master Data process and decision-making capabilities.
• Directed data cleansing and quality improvement efforts, leveraging ERP systems to achieve high data accuracy and streamlined operations.