What are the responsibilities and job description for the Senior Core Data Scientist position at SCOR?

Job Description

The Data Science Team has the responsibility of increasing our data science knowledge (survival analysis, model interpretability, etc) and spreading data science knowledge within the division. Representing the Data Science Chapter, the Data Science Team provides technical assistance (such as algorithmic or machine learning techniques) in business projects. As a member of the Data Science Chapter, the Senior Core Data Scientist will develop and manage advanced statistical, predictive, and machine learning models, as well as provide technical expertise to a growing cross-functional team of data scientists, underwriters, and actuaries. They will help innovate the medical underwriting process by creatively applying cutting-edge data science techniques.

Responsibilities

Support the development of advanced statistical, predictive, or machine learning models
Increase the interpretability of models through advanced understanding of artificial intelligence and machine learning
Explore cutting edge machine learning methods and tools
Be a key distributor of knowledge within SCOR globally, increasing the interpretability of models through an advanced understanding of artificial intelligence and machine learning
Make key contributions to the projects from the Americas market (US / Canada) as first priority but also be a core contributor on global projects, such as OCR, NLP, AutoML, visualization and templates
Collaborate with SCOR's thriving global data analytics community by being a key contributor on research projects
Spread data science knowledge internally and externally through seminars and publications
Present results to stakeholders; clearly communicate complex topics
Support the team on applying best practices in code development
Support strategic innovation initiatives for the Americas markets to transform processes (e.g. underwriting) from a machine learning perspective.
Adhere to all Information Security policies and best practices, including security awareness training and other information protection initiatives.
Have a high degree of autonomy when developing models and determining the appropriateness of a given approach

Qualifications

3-5 years' experience in data science with strong programming capabilities and advanced knowledge of supervised / unsupervised machine learning techniques

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.)

Strong critical thinking skills and ability to learn quickly

Ability to communicate, educate, and advise members of the global data science community 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.)

Good technical expertise on cloud computing platforms such as AWS and Microsoft Azure (or sufficient basics to learn quickly the usage of cloud technologies)

Expert knowledge of common data science programming languages such as Python (preferred) or R

Experience in using best practices for Python (unit tests, static typing, ...)

Experience in using CI / CD

Expert knowledge of OOP code architecture

Experience in usage of Docker and containerization

Experience in usage of distributed version control systems like Git

Experience of using machine learning to develop high-quality and practical solutions

Experience with database query tools such as SQL

Insurance industry experience is preferred, but not required

Actuarial exam progress is a plus

Experience in using Generative AI tools is a plus

Required Education

Master's degree (PhD is a plus) in science, technology, engineering, mathematics, computer science, actuarial science or similar quantitative field

Bachelor's degree plus actuarial qualifications, 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.

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