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# Data Scientist in Pricing

- **Company:** Allianz
- **Location:** Wien, Austria
- **Experience:** Experienced
- **Salary:** €60,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Big Data, Computer Programming, Databases, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Migration, Data Mining, Data Security, Decision Support Systems, DevOps, Python (Programming Language), Machine Learning, NumPy, SAS (Software), SQL Databases, Data Processing, Git, Pandas, Pyspark, Core Data, Scikit Learn, Information Technology, Data Analytics, Azure Synapse Analytics, Data Pipelines, Databricks
- **Published:** October 9, 2026
- **Apply:** https://www.xing.com/jobs/wien-data-scientist-pricing-158464633

## About the Role

* Education: Master's degree in Mathematics, Statistics, Physics, Computer Science, Data Science, Data Engineering, Econometrics, or a comparable STEM field.
 * Experience: big plus is a minimum 2 years of relevant professional experience in handling and processing large data volumes with Big Data frameworks, especially PySpark in Databricks, Azure Synapse, or Fabric. Interest in actuarial science and insurance business is a strong plus.
 * Programming & Tools: Strong proficiency in Python and core data science libraries (Pandas, NumPy, Scikit-Learn); experience with PySpark, SAS, SQL, or similar. Familiarity with DevOps practices (e.g., CI/CD pipelines, Git).
 * Data Expertise: Deep understanding of databases and data modeling, including data acquisition and integration, data security, data quality and accuracy, data migration, and related tools and processes.
 * Analytical & Creative Mindset: Strong analytical skills combined with a solution-oriented, creative approach to problem-solving.
 * Communication: Ability to clearly communicate complex issues to diverse stakeholders. Excellent English skills (C1) required; German is a strong plus.
 * Work Style: Self-driven, responsible, and passionate about lifelong learning with new technologies and methods - especially in the field of artificial intelligence.
 * Excellent English skills (C1). German is a plus but not mandatory

## Description

As a Data Scientist in Pricing, you will play a key role in shaping the future of insurance pricing through advanced analytics, machine learning, and data engineering. Working within agile, cross-functional teams in actuarial science, you will take end-to-end responsibility - from data architecture and pipeline development to stochastic modeling and tariff implementation. You will collaborate closely with other departments and international pricing colleagues to drive innovation and automation across the entire actuarial value chain.

Future fields of activity:

 * Stochastic Modeling & Tariff Development: Develop and refine stochastic forecasting models (risk, cancellation, and conversion models) and technical tariffs using state-of-the-art algorithms, including machine learning and data mining techniques.
 * Data Architecture & Engineering: Design and develop future-proof data architectures; build and optimize data models and data pipelines to support enterprise-wide analyses.
 * Data Quality & Governance: Ensure an adequate data foundation and meaningful KPIs for corporate steering; continuously improve ELT/ETL processes for efficient and reliable data processing.
 * AI & Machine Learning: Actively leverage AI and machine learning algorithms across all areas of the actuarial value chain - from data analysis and risk modeling to tariff development, reporting, and decision support. Drive the adoption of AI-powered solutions to enhance efficiency, accuracy, and innovation throughout the organization.
 * Product Development & Strategy: Actively shape product development and strategic initiatives within agile, cross-functional teams, taking on end-to-end responsibility.
 * Tooling & Dashboards: Create and expand tools and dashboards for actuarial analysis of quoted and completed contracts; conduct analyses and independently derive actionable recommendations.
 * Collaboration & Communication: Support data scientists and analysts in data-driven projects; prepare and present results to various stakeholders; exchange with international pricing colleagues on the latest developments.