Beschreibung
TätigkeitenbeschreibungFür unseren Kunden suchen wir einen Data Emgineer (m/w/d) für folgendes Projekt:
Determine the quality of risk and enable exposure management per Line of Business by building semi-automated risk assessment models
Increase the coverage of Risk Assessments in Underwriting portfolio through the utilization of external data sources
Automate data collection process in close alignment with Pricing Actuaries and other inhouse Data Engineers
Provide Allianz Risk Consulting and Underwriting full transparency of included elements/drivers in risk assessment model to ensure proper consideration
Identify and obtain required data from business stakeholders and translate business requirements into a working code
Create a centralized data lake from different internal and external data systems together with IT and other analytics stakeholders
Key Requirements/Skills/Experience:
Bachelor or Master Degree in a numerical field, preferably with a strong focus on Computer Science or Data Engineering, or qualified by experience
Several years of working experience in a data-focused role that requires rigorous financial or business analytics, ideally in a P&C environment
Proven history of data model design and implementation, ideally with a focus on P&C risk assessments
Knowledge of state of the art Underwriting processes and decision making frameworks
Significant experience in working with SQL essential
Strong expertise in Python, especially handling large datasets with pyspark
Excellent problem solving and analytical skills and likes to get hands on digging into data issues
Knowledge in Machine Learning / Data Science
Strong skills in data visualization and interpretation
Independent and self-directed individual that thrive when faced with challenge
Fluent English, any other language would be beneficial
Bei Interesse senden Sie uns einen aussagekräftigen WORD-CV in Anlehnung an die geforderten Skills, die konkrete und zugesicherte Verfügbarkeit und den Stundensatz (all incl.) zzgl. Ust. an Bitte mit Angabe der im Titel genannten Referenz Nr. (#xxxx). Für weitere Fragen stehen wir telefonisch unter u. g. Board zur Verfügung.
Ihr Ansprechpartner ist Herr Kastenmeier. Wir freuen uns auf Ihre Bewerbung!
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Fähigkeiten (Must have)
Consulting, Data Lake, Data Science, Design, Machine Learning, Python, SQL