Core Data Scientist

SCOR Group; Paris; Hybride; EUR 50 000 - 75 000; Plein temps

Résumé du poste

SCOR seeks a Core Data Scientist to deliver GenAI and ML models aligned with SCOR's AI strategy. You will join the Data & Analytics Office and work with business experts and clients to understand needs and build impactful AI solutions.

You will develop advanced models, apply lean delivery practices, and contribute to regional and global projects across NLP, GenAI, OCR, and visualization while ensuring data protection and regulatory compliance.

Qualifications

• 1–3 years’ experience in data science with ML techniques.

Responsabilités

• Develop advanced statistical, predictive, or ML models with robust coding practices.
• Hands-on delivery of projects and collaboration with clients and actuaries.
• Drive innovation in insurance through cross-functional teamwork and stakeholder alignment.
• Contribute to global/regional projects including NLP, GenAI, OCR, visualization.
• Support strategic initiatives and ensure on-time delivery with quality.
• Communicate results clearly to stakeholders with interpretable visuals.

Connaissances

Python

ML basics

Statistics

scikit-learn

Pandas

Docker

CoT prompts

AI agents

Formation

Master’s degree in STEM

Bachelor’s + ASA

Outils

Git

Docker

Description du poste

We are seeking a Core Data Scientist to deliverGenAI and machine learning models that align with our broader business & AI strategy. As part of a cross-functional delivery team, you work directly with business experts and SCOR clients, developing a strong understanding of their needs and build impactful AI models, in line with best practices on lean product delivery. You are part of the Data & Analytics Office, which drives the strategy, execution and governance of SCORs AI ambition, working in a global team of AI and data experts on some of SCORs (and SCOR’s clients) most important challenges and opportunities.

Responsibilities

Key duties and responsibilities

Approach

Develop advanced statistical, predictive, or machine learning models using deep knowledge of the algorithms and hyperparameters and systematically applying coding best practices.

Have a high degree of autonomy when developing models and determining the appropriateness of a given approach

Structure thoughts and guidelines in advance way when using agentic tools – being in capacity to challenge intermediate results, robustness and to manual reproduce specific outcomes for proper validation.

Projects

Being a hands-on and active doer in the delivery of projects

Help driving innovation in insurance areas through close collaboration with different parties including the client, underwriters, and actuaries.

Contribute to key topics of priority to the team and deliver on-time to agreed quality standards

Be a key contributor to regional market projects as first priority, but also a core contributor on global projects including OCR, NLP, Gen AI, visualization, templates, etc.

Support strategic innovation initiatives globally to transform process (e.g. underwriting) from a machine learning perspective.

R&D

Proactively identify relevant R&D for business needs

Be able to conduct research spikes to solve technical challenge

• Collaborate with SCOR’s thriving global data analytics community by being a key contributor on research projects and communication

Communication

Increase the interpretability of models through advanced understanding of artificial intelligence and machine learning

Present results to stakeholders; clearly communicate complex topics by applying appropriate interpretation techniques and visualizes these for the benefit of internal/external clients

As a member of the Data Science chapter, the Core Data Scientist will be an ambassador of the existing chapter and contribute to it (participating to training, maintain a certain level of knowledge by getting training as well on advance topics and developing skills): Be a key distributor of knowledge within SCOR globally

Spread data science knowledge externally through seminars and publications

Compliance

Adhere to all Information Security policies and best practices, including security awareness training and other information protection initiatives

Be fully compliant with GDPR and other local data protection legislation

Be aware of regulatory and reputational risk when developing consumer-facing AI tools and suggest ways of mitigating these

Qualifications

Required experience & competencies

• ~1-3 years’ experience in data science with solid programming capabilities and knowledge of supervised and unsupervised machine learning techniques
• Strong knowledge in statistics and basic models: mathematics (probability) + usage of libraries (sklearn, pandas)
• Uses Python in an advanced way (~go beyond notebooks, produce scripts, modules, POO, packaging)
• Capacity to use efficiently AI Agentic assistant in coding (setting skills, calibrating system prompts)
• Usage of Chain of Thoughts, prompting, and orchestration.
• Seek for answers by themselves by knowing the key concepts to look at (debugging code, google right terms, looking for proper help)
• Keeps up to date on academic research where relevant to business needs (reads ML/stats papers)
• Is able to industrialize ML models (e.g., git usage, basics on Docker) - or can quickly learn (~1/2 sprints)
• Understands and follows relevant data protection laws and best practice
• Being able to familiarize with new programming tools
• Insurance industry experience is preferred, but not required
• Shares and communicates about his/her work to rest of the technical team with accurate terms
• Documents his/her work (be able to write a technical report with explicit relevant and self-explicit charts, follow templates, etc.)
• High level controls on his/her work
• Proactively supports other team members with technical help and adopts a team mindset
• Is realistic with timeframes and updates relevant stakeholders on progress

Follows some quality standard when presenting / documenting / communicating

Business acumen

• Proactively identifies and raises technical concerns/doubts on data projects

Understands instructions and contributes to the vision by questioning or enriching the tasks defined during a project

Required Education

• Master’s degree (Ph. D. is a plus) in Science, Technology, Engineering, Mathematics, Computer Science, Actuarial or similar quantitative field
• Bachelor’s degree plus ASA or similar work experience is accepted in place of a relevant Master’s degree.

About Us

As a leading global reinsurer, SCOR offers its clients a diversified and innovative range of reinsurance and insurance solutions and services to control and manage risk. Applying “The Art & Science of Risk,” SCOR uses its industry-recognized expertise and cutting-edge financial solutions to serve its clients and contribute to the welfare and resilience of society in around 160 countries worldwide.

Working at SCOR means engaging with some of the best minds in the industry – actuaries, data scientists, underwriters, risk modelers, engineers, and many others – as we work together to find solutions to pressing challenges facing societies.

As an international company, our common culture is defined by “The SCOR Way.” Serving both to build momentum that drives the Group forward and as a compass to guide our actions and choices, The SCOR Way is anchored by five core values, reflecting the input of employees at all levels of the Group. We care about clients, people, and societies. We perform with integrity. We act with courage. We encourage open minds. And we thrive through collaboration.

SCOR supports inclusion and the diversity of talents, and all positions are open to people with disabilities.