Core Data Scientist

Employer: SCOR
Domain:
  • Insurances - Financial Intermediaries
  • Accounting - Finance
  • IT Software
  • Job type:: full-time
    Job level: 1 - 5 ani experienta
    Location:
  • BUCURESTI
  • Updated at: 22-09-2026
    Remote work: On-site

    We are seeking a Core Data Scientist to deliver GenAI 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.

    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

    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

    Communication skills

    • 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.

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