JUNIOR DATA SCIENTIST for Global P&C Pricing Team

Global P&C is an Allianz SE department established in 2011 as continuation of the Center of Competence project started in 2005. Its mission is supporting all Allianz P&C Entities to be outstanding in technical excellence by leveraging Allianz Capabilities.

Global P&C Pricing team is responsible for identifying, supporting implementation and ensuring standards, best practices and guidelines for data management, tariff development, portfolio analysis and monitoring. Specifically, the team oversees:

• Joint projects with the Allianz local entities around the world: we collaborate with local entities on pricing projects concerning mainly technical pricing, behavioural models, price optimization, scenario analysis, development of pricing and portfolio management tools.
• Research and development on Data & Analytics and tools to enhance the level of sophistication always considering the business relevance and impact
• Knowledge sharing and training of best practices: we design and facilitate P&C Pricing Academy courses to the wide community of pricing analyst of Allianz Group.
• Review activities: periodically we review the full pricing process of each local entity to ensure the standardization and harmonization of pricing processes and the implementation of best practices across the group.

KEY RESPONSIBILITIES

• Support the data ingestion, transformation, cleaning and exploration procedures
• Structuring data science solutions to achieve a given set of business objectives
• Build and prototype analysis and Machine Learning models and support their implementation and deployment in the systems of the company
• Model customer's behavior based on market and competitor's analysis
• Implement and enhance dashboards and business intelligence tools to support risk analysis and portfolio management
• Doing Research and Development to find new technical solutions
• Summarize, design and communicate effectively the results to both internal and external stakeholders
• Act as teacher for internal Pricing Academy courses

KEY REQUIREMENTS/SKILLS/EXPERIENCE

• PhD or Master's degree in a quantitative field (e.g., Computer Science, Mathematics, Physics, Statistics or Engineering)
• Fluent in Italian and English, written and spoken
• Work experience (e.g. 1 year)
• Valued international experience in both academic and professional settings
• Proficient in Python programming
• Experience with Pandas or SQL for data manipulation and analysis
• Familiarity with machine learning techniques like gradient boosting machines and linear models
• Experience on Quantum Optics topics (e.g. dissertation or papers) would be a plus
• Basic knowledge of Philosophy of Science topics would be a plus
• Experience with PySpark for large-scale data processing would be an advantage
• Passionate and skilled in data analysis and statistical modelling to support strategic decisions
• Excellent communication skill
• Demonstrated ability to work effectively as part of a diverse, multicultural and multidisciplinary team

Allianz Group is one of the most trusted insurance and asset management companies in the world. Caring for our employees, their ambitions, dreams and challenges, is what makes us a unique employer. Together we can build an environment where everyone feels empowered and has the confidence to explore, to grow and to shape a better future for our customers and the world around us. 
At Allianz, we stand for unity: we believe that a united world is a more prosperous world, and we are dedicated to consistently advocating for equal opportunities for all. And the foundation for this is our inclusive workplace, where people and performance both matter, and nurtures a culture grounded in integrity, fairness, inclusion and trust.
We therefore welcome applications regardless of ethnicity or cultural background, age, gender, nationality, religion, social class, disability or sexual orientation, or any other characteristics protected under applicable local laws and regulations.
Join us. Let's care for tomorrow.
Both genders may apply in accordance with the L. 903/77 (s.m.i).