Data Scientist in Advanced Analytics (m/w/d)

About Us

Welcome to Allianz.

Are you passionate about data and want to create real impact with your ideas at one of Germany's largest insurance companies?

As a Data Scientist (m/f/d), you will have the opportunity to answer exciting and relevant questions using a unique pool of insurance and health data in the German market and to integrate models developed by you into ongoing business processes. For this, we offer you a team of highly qualified and collaborative colleagues and we will foster and challenge you in your further development.

Become part of Allianz Private Krankenversicherungs AG - and shape the future with us in a dynamic growth market.

What awaits you as a Data Scientist in Advanced Analytics (m/f/d)

• Problem Solving & Strategy: You translate a business-relevant question into a statistical problem and identify the right framework for it.
• Data Engineering: You locate and combine data sources and transform large datasets for in-depth analysis.
• Modeling: You develop statistical and machine learning models and/or AI agents that automate decisions and integrate them into our core processes and systems.
• Communication: You interpret, visualize, and communicate your results understandably to top management, to subject matter colleagues (m/f/d), and to data scientists (m/f/d) in the APKV and beyond.
• Cross-Hierarchical Work: You work closely with APKV colleagues (m/f/d) from administration to management and understand the processes fully.
• Innovation: You recognize solutions and opportunities that others do not see and proactively drive them forward with your team.

What you bring as a Data Scientist in Advanced Analytics (m/f/d)

• Background: You have a university degree in statistics, mathematics, economics, computer science, engineering, physics, or a comparable discipline.
• Expertise: You have a deep understanding of the mathematical and statistical concepts behind the most common machine learning methods (e.g., linear models, decision trees, ensemble methods like Bagging and Boosting). You have a sound understanding of modern LLMs and Multi-Agent Architectures, including Prompt Engineering, Retrieval Augmented Generation (RAG).
• Practical Experience: You routinely program in Python (numpy, scipy, pandas, polars, matplotlib, scikit-learn) and SQL, develop modular, maintainable code and your own packages, and are proficient in handling tabular data across the entire pipeline - from exploration through feature engineering to modeling. You have experience working with GenAI and can translate strategic process requirements into scalable agentic end-to-end architectures.
• Technical Skills: You use Git, write automated tests, and are proficient in using CI/CD pipelines. Ideally, you have experience in using cloud infrastructure.
• Work Style (optional): You have already worked in agile and cross-functional teams.
• Language Skills: You have fluent German and fluent English language skills.

Our Highlights for You

• Health & Wellbeing: Company health insurance, sports and health offers, and prevention measures lay the foundation for physical and mental health.
• Compensation: Tariff special payments, company pension plan, capital-forming benefits, and employee shares make the compensation particularly attractive. Employees also participate in company success.
• Time & Flexibility: With our "New Work" model, work and private life can be balanced even better. We work flexibly, hybrid, mobile, and on-site.
• Career Development: We create a personal development plan together and enable you to gain cross-functional and international experience.

A complete overview of what makes us attractive as an employer can be found at careers.allianz.com/benefits.

Application

Start Date: As soon as possible

Have we sparked your interest and does this sound like an environment you would like to work in? Then apply now as a Data Scientist in Advanced Analytics (m/f/d) online on our career page - careers.allianz.com.

For technical and HR questions, you can reach your Recruiter Cintia Malnis at cintia.malnis@allianz.de.

Further information on the application process can be found here: Application Process Allianz in Germany.

Allianz in Germany has an internal recruiting team that focuses on directly sourcing outstanding candidates. Unsolicited applications from recruitment agencies or staffing firms are not accepted.

About Allianz

Since 1890, Allianz has been committed to the security of our customers and employees as a leading global insurer, financial services provider, and asset manager. Furthermore, Allianz has been regularly certified as a Great Place to Work since 2021 and recognized in the annual "Germany's Best Employers" competition. Our employees are important to us, and together we create a better world and future for ourselves and our customers.

Allianz Private Krankenversicherungs-AG is one of the largest medical insurers in Germany and the third-largest provider in the private insurance market. Become part of the team and enrich us with your personality. Let's care for tomorrow.

The Allianz Group is one of the world's leading insurance and asset management companies. We care for our employees, their goals, dreams, and challenges, making us a unique employer. Together, we create an environment where everyone feels supported and has the confidence to discover new things, develop, and shape a better future for our customers and the world around us.

At Allianz, we stand for cohesion: We believe that a united world is a sustainable world, and we are consistently committed to equal opportunities for all. The basis for this is our inclusive workplace, where both people and performance count, and a culture is cultivated that is based on integrity, fairness, inclusion, and trust.

We welcome applications from people of all ethnic and cultural backgrounds, age groups, genders, nationalities, religions, social backgrounds, people with or without disabilities, as well as diverse sexual orientations and other characteristics protected by local laws and regulations.

Join us. Let's care for tomorrow.