Senior Data Scientist – Cyber Risk Modelling

Job title:

Senior Data Scientist – Cyber Risk Modelling

Company

Adecco

Job description

Job Advert: Senior Data Scientist – Cyber Risk ModellingIndustry: InsuranceContract Type: PermanentWorking Pattern: Full Time, Hybrid working, 3 days in the Bristol officeOur client, a pioneering reinsurance agency based in Bristol, UK, is seeking a highly skilled and experienced Senior Data Scientist to join their dynamic modelling team. As a Senior Data Scientist, you will play a pivotal role in the development and operationalization of our client’s proprietary stochastic cyber risk model, contributing significantly to the advancement of their analytical capabilities and the broader field of cyber risk modelling.Key Responsibilities:

  • Model Development and Operation: Be a key member of the team responsible for the design, development, refinement, and execution of our client’s stochastic cyber risk model, ensuring its accuracy, performance, and scalability.
  • Data Analysis: Perform complex data analysis to extract insights and identify trends in cyber risk, utilising a variety of statistical and machine learning techniques.
  • Operationalization: Translate model insights into actionable strategies and tools for internal and external stakeholders.
  • Collaboration: Work closely with other team members, including underwriters, engineers, and cyber risk analysts, to integrate the cyber risk model with other systems and processes.
  • Innovation: Stay abreast of the latest developments in data science, cyber security, and risk modelling, and incorporate innovative techniques and technologies into our client’s models.

Qualifications:

  • Experience: At least 5 years of experience working as a data scientist/quantitative risk modeller, with a proven track record of operationalizing complex models and analytics.
  • Education: A degree in Computer Science, Engineering, Statistics, Mathematics, or a related field. Advanced degrees (MSc or PhD) are preferred.
  • Technical Skills: Expertise in applied machine learning, probability, statistics, and quantitative risk modelling. High level of proficiency in Python & SQL. Experience with big data technologies and tools, such as Databricks and Pyspark, is highly desirable. Experience of working in agile software development processes is a plus.
  • Industry Knowledge: Experience in insurance, cyber, or a related domain is ideal. Understanding of the reinsurance industry and its challenges is a plus.
  • Soft Skills: Excellent problem-solving abilities, strong communication skills, and the capacity to work effectively in a team-oriented environment.

The successful candidate will have the opportunity to make a tangible impact on the future of cyber risk management and reinsurance. They will work at the forefront of data science and cyber security, with opportunities to innovate and challenge the status quo. Our client offers professional development and advancement in a rapidly growing company, and values collaboration, support, and forward-thinking.Perks:

  • Health insurance
  • Hybrid working
  • Life assurance
  • Private Medical
  • 5% pension
  • 28 days annual leave, plus bank holidays
  • Career development
  • Competitive Salary

If you are a highly skilled and experienced Senior Data Scientist looking for an exciting opportunity to contribute to cutting-edge cyber risk modelling, we invite you to apply for this position. Must have full UK right to work without restrictions.To apply, please send your CV and cover letter to our agency. We look forward to hearing from you.Adecco is a disability-confident employer. It is important to us that we run an inclusive and accessible recruitment process to support candidates of all backgrounds and all abilities to apply. Adecco is committed to building a supportive environment for you to explore the next steps in your career. If you require reasonable adjustments at any stage, please let us know and we will be happy to support you.

Expected salary

Location

Bristol

Job date

Fri, 03 May 2024 03:22:49 GMT

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