Analyst & Data Analyst

Erfahrener Daten- und Business-Intelligence-Analyst mit Fachkenntnissen in ETL, Datenbanken und Business Intelligence. Erfahren in der Extraktion von Erkenntnissen aus Daten und der Implementierung von Prozessautomatisierung. Er unterstützt Unternehmen dabei, fundierte Entscheidungen zu treffen, indem er klare Datenanalysen erstellt. Beherrscht mehrere Sprachen und ist in SAS-Programmierung zertifiziert.

Head of Data Analytics & Reporting (Nov 2022 - Oct 2022)

• Managed comprehensive data and reporting functions for the company.
• Prioritized reporting needs based on urgency and integrated data from diverse sources.
• Developed a Golden Dataset in MS Power BI to enhance reporting efficiency.
• Implemented strategies to minimize ad-hoc reporting through dashboards and automation.
• Applied a Single Source of Truth (SSOT) approach to ensure data accuracy.
• Created modeling tools for forecasting and cash flow planning.
• Provided valuable insights across various business domains.

Business Intelligence Consultant (Jul 2021 - Apr 2022)

• Involved in end-to-end support for clients in data and automation.
• Analyzed client requirements and recommended suitable tools.
• Prepared price quotations and developed data models in Power BI.
• Designed report layouts and visuals tailored to different industries.
• Deployed and trained users in operating reports and Power BI.
• Developed custom solutions using Robotic Process Automation (RPA).

Credit Risk Analyst (Jul 2019 - Jun 2021)

• Extracted and interpreted data from a large relational database.
• Streamlined SQL scripts, functions, and procedures (MSSQL Server).
• Utilized various tools, including MS Office, Power BI, and Visual Studio for reporting.
• Designed SSIS and SSRS packages for tables and daily reports.
• Evaluated and enhanced methods for calculating key performance indicators (KPIs).
• Applied Python for outlier detection in loan application data.

Data Scientist (Sep 2018 - Jun 2019)

• Conducted data analysis in diverse industries, including healthcare and banking.
• Cleaned and pre-processed data using PySpark, performed feature engineering.
• Implemented supervised and unsupervised machine learning algorithms.
• Worked on tasks such as sequence prediction, anomaly and fraud detection, and image classification.
• Presented findings in a clear and understandable manner using visualization tools