
Christian Streibl
Fähigkeiten und Kenntnisse
Werdegang
Berufserfahrung von Christian Streibl
- Current 3 years, since Jun 2023
Co-Founder / CDAO & CFO
FBS-Systems
Wir ermöglichen die Energiewende - mit Speicherkapazität & Flexibilität. Projektentwicklung von Großbatteriespeichern & Beratung
Participation in the Deloitte Analytics Journey: Financial Advisory / M&A Transactions Services (Jun 22 – Sep 22) • Simulation of a large and realistic demo sales dataset in R • Data analysis and visualization in QlikSense & PowerBI Risk Advisory (Oct 22 – Jan 23): • Building a software tool to quickly and automatically analyze customer spend cubes using Python. Consulting / Center for Process Bionics (Feb 23 – Jun 23): • Process mining and process automation with QlikSense and MPM Process mining
- Identifying BI-potentials for Operations departments & teams - Controlling Support in Data Analytics & Business Intelligence - Implementation of Power BI and creation of dashboards and reports - SYNCPILOT process Landscape support - Power BI / Excel Support - Perform Tool workshops (Excel/Power BI) - Identifying automation potentials for Operations Departments & Teams
Productmanagement and Data Analytics - Creating analyses (e.g. on booking figures, customer behavior) and statistical evaluations (e.g. A/B testing) with Excel and QlikView - Creation of ad-hoc reports for the management, the product management and the business intelligence team - Data preparation with R
Ausbildung von Christian Streibl
- 2 years, Nov 2020 - Oct 2022
BWL
Universität Augsburg
Quantitative study with Major Finance and Information and courses in Econometrics, financial engineering and machine learning. Master thesis at the Chair of Statistics with the topic: "Exchange power price forecasting on the German energy market using neural networks and meteorological parameters" in cooperation with the startup alitiq.
- 3 years and 1 month, Oct 2017 - Oct 2020
Betriebswirtschaftslehre
Universität Augsburg
Quantitative study with Major Finance and Information and courses in data mining, data analysis, corporate finance, risk management, statistics, and financial mathematics. Final grade: 1.82
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