Senior Core Data Scientist

SCOR; Paris; Sur place; EUR 60 000 - 80 000; Plein temps

Résumé du poste

A prominent insurance firm in Paris seeks a Senior Core Data Scientist to develop advanced statistical and machine learning models in the Life & Health domain. You will work with cross-functional teams and contribute to innovative underwriting processes, applying your strong programming skills and insurance knowledge. A master's degree in a quantitative field and several years of experience in data science are essential. This role offers significant opportunities for impact and collaboration within a global team.

Qualifications

• 3-5 years’ experience in data science.
• Insurance industry experience required.
• Ability to perform code peer reviews.

Responsabilités

• Develop advanced statistical and machine learning models.
• Drive innovation in the underwriting process.
• Communicate results and explain complex topics.

Connaissances

Strong programming capabilities

Advanced knowledge of supervised machine learning

Python expertise

Critical thinking skills

Good communication skills

Formation

Master's degree in a quantitative field

Outils

AWS

Microsoft Azure

Description du poste

We are seeking a Senior Core Data Scientist with a focus on Life & Health domain knowledge to deliveradvanced statistical, predictive, and machine learning models that align with our broader L&H business & AI strategy. As part of a cross-functional delivery team (underwriters, medical doctors, actuaries, machine learning engineers, etc.), you work directly with business experts and SCOR L&H 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 most important challenges and opportunities.

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 an understanding of L&H actuarial technics (Experience Analysis, survival modelling) and embed them into relevant modelling approach.
• Have a high degree of autonomy when developing models and determining the appropriateness of a given approach

Projects

• Help driving innovation in the underwriting process through close collaboration with different parties including the client, underwriters, and actuaries.
• Own topics of priority to the team and deliver on-time to agreed quality standards
• Be a key contributor to all predictive UW and claims related projects supporting all regions and internal / external clients.
• Support strategic innovation initiatives globally to transform process (e.g. underwriting, claims) from a machine learning perspective.
• Proactively identify relevant R&D for business needs
• Collaborate with SCOR’s thriving global AI community by being a key contributor on research projects

Communication

• Increase the interpretability of models through advanced understanding of AI and machine learning
• Present results to stakeholders and explain complex topics clearly using suitable interpretation methods for clients.
• As a member of the Data Science chapter, the Senior 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

Required experience & competencies

• 3-5 years’ experience in data science with strong programming capabilities and advanced knowledge of supervised and unsupervised machine learning techniques
• Insurance industry experience is required
• Can perform code peer reviews and merge requests
• Strong critical thinking skills and ability to learn quickly
• Good technical expertise on cloud computing platforms such as AWS and Microsoft Azure (or sufficient basics to learn fast the usage of cloud technologies)
• Expert knowledge of Python
• Experience using machine learning to develop high-quality and practical solutions
• Deep understanding of predictive modeling concepts, machine-learning approaches, clustering, classification and crowdsourcing techniques (e.g GLMs, Decision Trees, SVM, Random Forests, GBM, PCA, Bayesian Networks, Neural Networks, etc.) applied to L&H
• Ability to communicate, educate, and advise colleagues and clients on predictive modeling concepts, machine-learning approaches, clustering, classification and crowdsourcing techniques (e.g GLMs, Decision Trees, SVM, Random Forests, GBM, PCA, Bayesian Networks, Neural Networks, etc.)
• Ability to adapt communication style to the level of technical expertise of the audience

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.