At a Glance
- Tasks: Validate climate risk models and conduct quantitative analysis to ensure data integrity.
- Company: AMS partners with a major UK retail bank focused on inclusive workplaces.
- Benefits: Hybrid working model, competitive pay, and opportunity to impact sustainability.
- Other info: 3-month contract with potential for growth in a dynamic environment.
- Why this job: Join a mission-driven team tackling climate risk in the financial sector.
- Qualifications: Expertise in climate risk and advanced Python skills required.
The predicted salary is between 50000 - 70000 £ per year.
AMS is a global workforce solutions partner committed to creating inclusive, dynamic, and future-ready workplaces.
We help organisations adapt, grow, and thrive in an ever-evolving world by building, shaping, and optimising diverse talent strategies.
Our Contingent Workforce Solutions (CWS) is one of our service offerings.
Acting as an extension of their recruitment teams, we connect them with skilled interim and temporary professionals, fostering workplaces where everyone can contribute and succeed.
Our client, a major UK retail bank, provides every day banking services to over 17 million retail customers.
The banks expertise and services span across Business Services, Corporate banking, Wealth Management, Group Functions, Retail and Investment Banking.
On behalf of this organisation, AMS are looking for a Data Scientist for a 3 month contract based in Edinburgh with remote working available (Hybrid).
Purpose of the role: We are seeking an experienced Data Scientist with specialist expertise in Climate Risk, Transition Planning and Sustainability Modelling to provide independent oversight and challenge of the organisation's data-driven models.
You will be responsible for conducting robust model validations, quantitative analysis and governance reviews across climate risk models, ensuring that model risks are identified, assessed and appropriately managed.
What you'll do: Perform independent validation of climate risk, forecasting, scenario analysis, stress testing and optimisation models.
Conduct quantitative analysis, sensitivity testing and model reviews to assess performance, robustness and fitness for purpose.
Evaluate model assumptions, methodologies, data quality, uncertainty and limitations, ensuring model risks are clearly identified and documented.
Assess compliance with regulatory requirements, including PRA SS1/23, and internal model risk standards.
Review model sub-components and controls, preparing validation checklists and governance documentation.
Produce high quality validation reports and papers for senior management, regulators and auditors.
Provide expert advice on climate risk modelling, transition planning and sustainability related analytics.
The skills you'll need: Strong expertise in climate risk, climate scenarios, decarbonisation pathways, net-zero strategies and emerging sustainability regulations.
Experience independently validating complex quantitative models, ideally within financial services.
Strong understanding of model risk management frameworks and governance.
Advanced Python skills for data manipulation, analysis and model assessment.
Experience reviewing and auditing model builds, with the ability to understand and challenge underlying model mechanics.
Degree in a quantitative discipline such as Mathematics, Statistics, Data Science, Economics, Engineering or Physics.
Next steps This client will only accept workers operating via an Umbrella or PAYE engagement model.
If you are interested in applying for this position and meet the criteria outlined above, please click the link to apply and we will contact you with an update in due course.
AMS, a Recruitment Process Outsourcing Company, may in the delivery of some of its services be deemed to operate as an Employment Agency or an Employment Business TPBN1_UKTJ
Data Scientist (Climate Risk) in Bonnyrigg employer: AMS CWS
At AMS, we pride ourselves on being an exceptional employer that champions inclusivity and diversity in the workplace. Our partnership with PwC allows us to offer meaningful roles like the SAP Analytics Cloud (SAC) Planning Lead, where you can thrive in a high-performance culture that values ethical standards and professional growth. With flexible remote working options and a commitment to employee development, we empower our team members to make a significant impact while enjoying a supportive and dynamic work environment in London.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist (Climate Risk) in Bonnyrigg
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like AMS CWS before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
✨Check Out Specialist Job Boards
For temp roles, hit up job boards dedicated to tech and data science, like Stack Overflow Jobs or DataJobs. These platforms often feature openings that you won’t find on general job sites, including contracts with companies like AMS CWS.
✨Leverage University Resources
If you're currently at uni or recently graduated, tap into your school's career services. They often have connections with companies looking for temporary data science interns or contract workers, and they might even host job fairs with employers like AMS CWS.
We think you need these skills to ace Data Scientist (Climate Risk) in Bonnyrigg
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at AMS CWS, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to AMS CWS, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab AMS CWS’s attention and show the tangible impact of your work.
How to prepare for a job interview at AMS CWS
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at AMS CWS.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at AMS CWS.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at AMS CWS.
