Welcome to my digital business card!

As an expert in Controlling and Finance, I specialize in optimizing financial processes through digital methods. This online portfolio showcases my career journey and demonstrates innovative solutions in modern finance and data science.

Feel free to navigate through the various sections and contact me if you have any questions or are interested in collaboration. I look forward to connecting with you!

Experience

Plastics Unbound

Upon Request
2023 - today

Other

Finance Transformation

  • Systems: Facilitation of large scale ERP migration projects in the area of Finance and Risk (MS Dynamics, ProAlpha, Powercurve/NBSM).

  • Processes: Development and implementation of new processes in the area of finance (e.g. O2C, R2R etc.).

Finance Operations

  • Finance, Planning & Analysis: Development and management of budgeting and month-end closing processes

Domain Know-How

  • BIG4, Insurance, Payments und Engineering

2010 - 2022

Education

Georg-August-University Göttingen

MSc Business Administration
Courses included: Corp. Finance, Fin. Acounting, Inv. Mgmt, Econometrics and Statistics
Thesis: "Publicity and Information Asymmetries - Measurement of the Capital Market Effects of Publicity by Using Proxies" Grade: 1.3 Download

Grade: 1.59

2005 - 2010

University of California, Berkeley

Business Administration - EAP Stipendium
Courses included: accounting, corporate finance (a.o.)

2007 - 2008

Skills

# Languages Level
1 German
2 English
3 Persian

# Tool Level
1 SAP FI/CO
2 MS Dynamics 365
3 MS Power Query, Power Pivot, Power BI
4 (MS/Postgres) SQL
5 IBM Cognos

# Language Level
1 R / RStudio
2 Python
3 VBA Excel
3 Javascript/JQuery

# Tool Level
1 MS Sharepoint
2 Confluence
3 Atlassian JIRA
4 Git/Github

Variables

  • n: absolute frequency of the selected name

Remarks

  • The data pertains to the United States of America.
  • The analysis allows for the selection of any given first name.
  • The graph displays the annual frequency of the chosen name.

Variables

  • prop: Corresponds to the relative frequency of the selected name

Remarks

  • The ranking is based on U.S. data
  • The evaluation reflects the most frequently chosen names of newborns in the U.S.

Variables

  • tf_idf: TF-IDF (Term frequency-inverse document frequency), statistic reflects the importance of an ingredient for the respective cuisine.

Remarks

  • Wordcloud: The size of the words represents the frequency of use of the ingredients in the selected cuisine.