AI Validation Specialist (Data Scientist)

Náplň práce, právomoci a zodpovednosti:
Are you passionate about ensuring AI systems are trustworthy and reliable? Join us as an AI Validation Specialist (Data Scientist), where you will assess AI/ML solutions across Swiss Re and support teams in strengthening their quality and robustness. In this role, you’ll apply your analytical and data science skills to ensure that models are technically sound, transparent, and aligned with responsible AI principles.

About the Role 

You will deep-dive into real AI use cases, from business framing and data quality to model design, evaluation methodologies and results, and help shape how Swiss Re develops and deploys AI safely and effectively. If you enjoy rigorous reasoning, asking the right questions, and getting to the bottom of how models truly work, this role is for you.

Key Responsibilities:

- Review AI/ML use cases developed across Swiss Re, analysing business objectives, data quality, feature engineering, modelling choices, evaluation methodology and results.
- Identify methodological, technical, or ethical issues in model documentation and raise targeted questions to ensure clarity, soundness, and completeness.
- Prepare structured validation reports that summarise findings, risks, and recommendations for improving model robustness, transparency, and alignment with responsible AI principles.
- Contribute to the development of evaluation guidelines and best practices, including for emerging areas such as Agentic AI.
- Support AI red teaming activities for GenAI use cases by probing model behaviour, prompting vulnerabilities, and documenting risks.
- Help improve internal validation processes and tooling, identifying opportunities to streamline workflows and strengthen our AI governance framework.
- Stay current with developments in machine learning, evaluation methodologies, and AI governance, applying new insights to validation work.

About the Team 

We are the stewards of responsible AI. Our team ensures that AI systems are not only powerful and innovative, but also safe, transparent, and aligned with regulatory expectations. From shaping internal policies to validating AI systems, we bridge the gap between cutting-edge technology and trustworthy deployment. 

Zamestnanecké výhody, benefity:
You can look forward to extra rewards and benefits including:
- Attractive performance-based bonus
- Ultra flexible working time in hybrid setup, allowing you to work also from home
- Modern office spaces in attractive location
- 5 additional days of holiday
- Lunch allowance fully paid by Swiss Re
- Referral bonus
- Pension & risk insurance contribution
- Sick days and sick leave support
- Public transport benefit
- Multisport card

Informácie o výberovom konaní:
We are an equal opportunity employer, and we value diversity at our company. Our aim is to live visible and invisible diversity – diversity of age, race, ethnicity, nationality, gender, gender identity, sexual orientation, religious beliefs, physical abilities, personalities and experiences – at all levels and in all functions and regions. We also collaborate in a flexible working environment, providing you with a compelling degree of autonomy to decide how, when and where to carry out your tasks.

We provide feedback to all candidates via email. If you have not heard back from us, please check your spam folder.

Požiadavky na zamestnanca:
About You

You are a curious and analytical thinker with a strong interest in how AI and machine learning systems are built and evaluated. You enjoy digging into details, asking thoughtful questions, and approaching problems with a structured and responsible mindset. You work well with others, communicate clearly, and are motivated to continuously learn and grow in a rapidly evolving field.

We are looking for candidates who have:

- A degree in Mathematics, Data Science, Computer Science, Statistics, Physics, Engineering, or another quantitative field
- Solid understanding of machine learning concepts, methodologies, and evaluation principles
- Practical experience implementing machine learning models, proficiency in Python and familiarity with ML libraries
- Curiosity and the ability to reason critically about model assumptions, data quality, and evaluation approaches
- Strong communication skills, with the ability to ask precise questions and explain technical conclusions clearly
- A detail-oriented mindset and a commitment to quality and transparency

These are additional nice to have: 

- Experience with AI governance frameworks or validation methodologies
- Knowledge of regulatory requirements related to AI systems
- Familiarity with model documentation standards
- Experience in a regulated industry (finance, healthcare, etc.)

We welcome candidates at all experience levels, including recent graduates with the right foundation. If you don't meet all requirements but are eager to learn, we encourage you to apply!