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- Tasks: Develop and implement loss models for environmental risks like floods and wildfires.
- Company: Join a mission-driven impact tech company backed by top-tier venture capital.
- Benefits: Enjoy hybrid working, competitive salary, equity options, and comprehensive benefits.
- Why this job: Make a real difference in tackling climate challenges while working with a world-class team.
- Qualifications: PhD or equivalent experience in climate science, with 3+ years in related modelling domains.
- Other info: Opportunity to represent the team at industry events and engage externally.
The predicted salary is between 51000 - 68000 £ per year.
Hybrid (London – 3 days on-site)
Series A Impact Tech Business
£60k - £80k + Meaningful Equity
Albany Growth are partnering with a mission-led impact tech focused company backed by a top-tier VC who are looking to expand out their world class research and science team and as a result are looking for a Data Scientist with specific experience in loss modelling. This role is ideal for someone with experience in catastrophe or physical risk modelling, applied statistics, and geospatial data. You’ll play a key role in shaping the loss modelling framework behind a next-generation SaaS platform used by global clients across banking, insurance, and real estate.
Key Responsibilities
- Develop and implement robust, scientifically grounded loss models across things such as floods, storms, droughts, and wildfires
- Calibrate and validate models using large geospatial and financial loss datasets
- Help shape a flexible loss modelling framework adaptable across global markets
- Collaborate with stakeholders to communicate modelling approaches and outputs
- Represent the team at industry events and contribute to external engagement
Key Requirements
- Strong experience in catastrophe or loss model development and calibration
- Applied statistical background with ability to validate models both quantitatively and qualitatively
- Proficiency with geospatial data, Earth Observation sources, and climate datasets
- Skilled in Python, R, or similar programming language
- Excellent communication skills, with the ability to explain technical concepts clearly
- PhD or equivalent experience in climate science, hazard modelling, remote sensing, or statistical modelling
- 3+ years of experience in climate risk, catastrophe, or related modelling domains
Bonus Experience
- Expertise in exposure and vulnerability within catastrophe models
- Background in Bayesian statistics, Extreme Value Theory, or uncertainty quantification
- Knowledge of machine learning techniques for climate risk
- Familiarity with cloud computing (AWS, GCP)
Hybrid working (3 days/week on-site in London) £65k - £80k base + very good equity + comprehensive benefits. Mission-led company tackling environmental risk with science and software. Series A stage with strong customer traction across financial services.
If you’re excited about applying scientific rigour to tackle one of the world’s most urgent challenges, apply using the link and we’ll be in touch with more details.
Data Scientist (Loss Modelling) employer: Albany Growth
Contact Detail:
Albany Growth Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist (Loss Modelling)
✨Tip Number 1
Network with professionals in the climate risk and catastrophe modelling fields. Attend industry events or webinars where you can meet potential colleagues and learn more about the latest trends and challenges in loss modelling.
✨Tip Number 2
Showcase your technical skills by contributing to open-source projects or creating a portfolio of your work related to geospatial data analysis and loss modelling. This will demonstrate your practical experience and passion for the field.
✨Tip Number 3
Prepare to discuss your previous projects in detail during interviews. Be ready to explain your approach to model development, calibration, and validation, as well as how you’ve communicated complex concepts to non-technical stakeholders.
✨Tip Number 4
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Python, R, and cloud computing platforms. Being able to speak confidently about these tools will set you apart from other candidates.
We think you need these skills to ace Data Scientist (Loss Modelling)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in catastrophe or loss model development. Emphasise your applied statistical background and any relevant projects involving geospatial data.
Craft a Compelling Cover Letter: In your cover letter, express your passion for tackling environmental risks through science and software. Mention specific experiences that align with the key responsibilities of the role, such as developing loss models for natural disasters.
Showcase Technical Skills: Clearly outline your proficiency in programming languages like Python or R. If you have experience with machine learning techniques or cloud computing, make sure to include that as well.
Highlight Communication Skills: Since excellent communication skills are crucial for this role, provide examples of how you've effectively communicated complex technical concepts to non-technical stakeholders in the past.
How to prepare for a job interview at Albany Growth
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in Python, R, and any other relevant programming languages. Be prepared to discuss specific projects where you've applied these skills, especially in loss modelling or catastrophe risk.
✨Demonstrate Your Understanding of Geospatial Data
Since the role involves working with geospatial data, be ready to explain how you've used such data in previous projects. Discuss any experience you have with Earth Observation sources and climate datasets, as this will be crucial for the position.
✨Prepare for Scenario-Based Questions
Expect questions that assess your ability to develop and validate loss models. Prepare to walk through your thought process on how you would approach modelling for different scenarios like floods or wildfires, showcasing your analytical skills.
✨Communicate Clearly and Effectively
Excellent communication skills are essential for this role. Practice explaining complex technical concepts in simple terms, as you'll need to collaborate with stakeholders and represent the team at industry events.
