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- Tasks: Dive into data to drive predictive analytics and support business growth.
- Company: Join a leading firm focused on innovative insurance solutions in London.
- Benefits: Enjoy a permanent position with opportunities for professional growth and development.
- Why this job: Be part of a dynamic team using cutting-edge technology to make impactful decisions.
- Qualifications: Must have a degree in a relevant field and experience in statistical modeling and machine learning.
- Other info: Experience in life or health insurance is a plus!
The predicted salary is between 43200 - 72000 £ per year.
Responsible for supporting the delivery of Predictive Analytics initiatives to support growth across all its lines of business by harnessing data-model-driven insights to meet their ambitions.
- Location: London
- Category: Data
- Type: Permanent
Key Duties (including but not limited to):
- Provision of advanced pensioner demographics and mortality basis based on optimal exploitation of newly acquired data sets, enabling a build-up of a competitive Flow proposition, and enhancing accuracy and efficiency to expand the overall Longevity business portfolio.
- Identify potential solutions to support the Protection line of business on new propositions across underwriting, claims, and distribution where Predictive Analytics can deliver new insights and solutions to reduce friction.
- Conceptualize and offer analytics products and services to internal and external stakeholders along the whole value chain by using modern statistical methods like GLM, machine learning, and where applicable, Knowledge Graphs and Large Language Models.
Minimum Requirements:
- Degree, Master’s degree, or Ph.D. in a relevant field such as Computer Science, Statistics, Economics, or Applied Mathematics.
- Practical experience in statistical modelling, machine learning, text mining, and data visualization tools.
- Previous experience in life or health insurance, direct and/or reinsurance is desirable.
- Proficiency in data manipulation, statistical analysis, and predictive modelling using tools such as R, Python, SAS, or similar.
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Data Scientist – 28211 employer: The Emerald Group
Contact Detail:
The Emerald Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist – 28211
✨Tip Number 1
Familiarize yourself with the specific predictive analytics tools and techniques mentioned in the job description, such as GLM and machine learning. Being able to discuss these methods confidently during your interview will show that you are well-prepared and knowledgeable.
✨Tip Number 2
Highlight any relevant projects or experiences where you've successfully applied statistical modeling or machine learning in a business context. This will demonstrate your practical experience and ability to deliver insights that can drive business growth.
✨Tip Number 3
Research the company’s current initiatives in predictive analytics and longevity business. Understanding their goals and challenges will allow you to tailor your discussions and suggest how your skills can directly contribute to their success.
✨Tip Number 4
Network with professionals in the life or health insurance industry, especially those who work with predictive analytics. Engaging with them can provide valuable insights and potentially lead to referrals that could enhance your application.
We think you need these skills to ace Data Scientist – 28211
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description for the Data Scientist position. Understand the key duties and minimum requirements, and think about how your skills and experiences align with them.
Highlight Relevant Experience: In your CV and cover letter, emphasize your practical experience in statistical modeling, machine learning, and data visualization tools. Mention any specific projects or roles that relate directly to the responsibilities outlined in the job description.
Showcase Technical Skills: Clearly list your proficiency in relevant programming languages and tools such as R, Python, and SAS. Provide examples of how you've used these tools in past projects to solve problems or deliver insights.
Tailor Your Application: Customize your cover letter to reflect your understanding of the company's goals and how you can contribute to their Predictive Analytics initiatives. Use specific language from the job description to demonstrate your fit for the role.
How to prepare for a job interview at The Emerald Group
✨Showcase Your Technical Skills
Be prepared to discuss your experience with statistical modeling, machine learning, and data visualization tools. Highlight specific projects where you've successfully applied these skills, especially using R or Python.
✨Understand the Business Context
Research the company’s lines of business and how predictive analytics can enhance their operations. Be ready to discuss how your insights can support growth and improve efficiency in their longevity business portfolio.
✨Prepare for Problem-Solving Questions
Expect questions that assess your ability to identify solutions for underwriting, claims, and distribution challenges. Think of examples where you’ve used data-driven insights to solve real-world problems.
✨Communicate Clearly and Effectively
Practice explaining complex analytical concepts in simple terms. You may need to present your ideas to stakeholders who may not have a technical background, so clarity is key.
