Catastrophe Risk Analyst - Property Analytics, Reinsurance

Aon Corporation; London; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A leading global risk management firm in London is looking for a Catastrophe Risk Analyst to join their Property Analytics team. The role involves using data science and machine learning to assist clients with natural disaster risk assessments. Candidates should possess an MSc in Data Science and have solid coding skills. This position offers the flexibility of hybrid working arrangements and a supportive work environment.

Benefits

Comprehensive benefits package

Global Wellbeing Days

Flexible working options

Qualifications

• MSc or higher qualification ideally in Data Science and Machine Learning.
• Experience in (re)insurance and catastrophe modelling is ideal.
• Proficiency in analytical tools like Pandas and Scikit-learn.

Responsibilities

• Use machine learning and data science to enhance analytical tools.
• Conduct sophisticated spatial analyses and develop predictive models.
• Mentor junior team members in geospatial programming skills.

Skills

Data Science

Machine Learning

Strong communication skills

Coding in Python

Familiar with CI/CD platforms

Experience with Tableau

Education

MSc in Data Science or Machine Learning

BSc in Geography and/or Risk

Tools

Python

SQL

R

ArcGIS

PowerBI

Job description

Catastrophe Risk Analyst, Property Analytics, Reinsurance

Want to join a top Catastrophe Property Analytics team to advise clients on natural disaster risks?

Can you bring an advanced qualification in Data Science and Machine Learning underpinned by practical coding, IT and data skills? If so, we'd love to hear from you in connection with this brand-new role that comes with the flexibility to work both virtually and from our London office!

Aon is in the business of better decisions

At Aon, we shape decisions for the better to protect and enrich the lives of people around the world. As an organisation, we are united through trust as one inclusive team, and we are passionate about helping our colleagues and clients succeed.

What the day will look like

In this wide and varied role your responsibilities will include:

• Use machine learning and data science to contribute to the suite of proprietary analytical and efficiency tools developed by Aon UK team
• Conduct sophisticated spatial analyses and develop predictive models to uncover patterns, trends, and actionable solutions, supporting the creation of proprietary tools and datasets.
• Support client renewals, developing knowledge of cat and non-cat analytics, running all vendor models (e.g. RMS, Verisk, JBA, Impact Forecasting, CoreLogic).
• Clearly communicate insights, findings, and recommendations to technical and non-technical collaborators.
• Assist in the evolution of Aon's UK Event Response solutions, calculating client's potential incurred losses, post-event and on risk management basis.
• Participate in corporate practice groups and committees related to cat modelling, data science, ML, and cat risk management.
• Mentor and support junior team members in building their geospatial programming skills and technical expertise.

How this opportunity is different

Aon's Catastrophe Analytics team is the best regarded of its kind in Europe. The team sits within Aon Reinsurance Solutions and provides clients (UK insurance companies, syndicates and reinsurers) with advice on their underlying risks, and exposures to natural disasters such as windstorms, floods and earthquakes.

Comprised of enthusiastic and team-oriented individuals, the UK Property team is continuously looking for ways to evolve our clients' understanding and view of catastrophe risk. Working very closely with our brokers, academic partners and our model evaluation specialists enables us to perform and draw from expert analysis and experience to make better decisions for our clients.

Skills and experience that will lead to success

Experience:

• MSc or higher qualification ideally in Data Science and Machine Learning.
• BSc in Geography and/or Risk.
• (Re)insurance and Catastrophe modelling knowledge/experience ideal.
• Experienced in leveraging open-source datasets to develop analytical tools and insights.
• Familiar with CI/CD and DevOps platforms, including GitLab and Microsoft Azure

Skills:

• Strong communication skills (speaking, listening, and writing)
• Proficient data scientist with expertise in key frameworks and libraries, for example: Pandas, Geopandas, Rasterio, Apache Sedona, Mosaic, Scikit-learn, PyTorch; or equivalent.
• Coding skills in Python, SQL, R
• ArcGIS / Mapping Tools
• Tableau or PowerBI experience

How we support our colleagues

In addition to our comprehensive benefits package, we encourage an inclusive workforce. Plus, our agile environment allows you to manage your wellbeing and work/life balance, ensuring you can be your best self at Aon. Furthermore, all colleagues enjoy two "Global Wellbeing Days" each year, encouraging you to take time to focus on yourself. We offer a variety of working style solutions for our colleagues as well.

Our continuous learning culture inspires and equips you to learn, share and grow, helping you achieve your fullest potential. As a result, at Aon, you are more connected, more relevant, and more valued.

Aon values an innovative and inclusive workplace where all colleagues feel empowered to be their authentic selves. Aon is proud to be an equal opportunity workplace.

Aon provides equal employment opportunities to all employees and applicants for employment without regard to race, colour, religion, creed, sex, sexual orientation, gender identity, national origin, age, disability, veteran, marital, domestic partner status, or other legally protected status.

We are committed to providing equal employment opportunities and fostering an inclusive workplace. If you require accommodations during the application or interview process, please let us know. You can request accommodations by emailing us at [e-mail] or your recruiter. We will work with you to meet your needs and ensure a fair and equitable experience.

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