At a Glance
- Tasks: Develop and validate AI prototypes for sustainability insights and carbon markets.
- Company: Join CarbonAI, a leader in sustainability intelligence and innovation.
- Benefits: Competitive salary, flexible remote work, and opportunities for professional growth.
- Other info: Collaborative environment with exposure to product strategy and senior decision-makers.
- Why this job: Make a real impact on sustainability while working with cutting-edge AI technology.
- Qualifications: 2-4 years in data science, strong Python and SQL skills, and a customer-focused mindset.
The predicted salary is between 45000 - 55000 £ per year.
Location
Remote, with occasional visits to the London office
Type
- Full-time
- Reports to : Head of Data Science
Salary
£45,000-£55,000 per year, depending on experience.
About Carbon AI
Carbon AI is a sustainability intelligence platform helping organisations make better-informed decisions on ESG, carbon markets and sustainability.
We combine data, AI and expert research across ratings, indicators, dashboards and AI research tools.
The role
We are looking for a hands-on Data Scientist to develop and validate data and AI prototypes that help customers understand complex sustainability and carbon-market information.
You will work with product, engineering, sales and sustainability experts to explore customer needs, test new ideas and provide clear prototypes and requirements for Engineering to implement in production.
What you will do
- Develop and validate data-science, NLP and AI prototype workflows, including extracting and structuring information from sustainability reports, carbon-project documents, methodologies, registries and regulatory materials.
- Contribute to improvements in AI-powered features and analytical tools using retrieval, document-analysis and information-extraction capabilities.
- Support predictive modelling, data-quality checks and geospatial analysis across climate, environmental and carbon-market datasets.
- Help translate client feedback and customer workflows into product requirements, working alongside product and sales colleagues.
- Contribute to R&D on emerging data and AI approaches, and on sustainability and carbon-market trends, using customer and market insights to suggest new product capabilities or improvements.
- Work with Engineering to provide validated prototypes, implementation requirements and evaluation criteria, and communicate findings clearly to colleagues and, where appropriate, clients.
- What we are looking for
- Roughly 2-4 years of commercial experience in data science, AI engineering or a closely related role.
- Strong Python and SQL skills, plus practical experience in NLP, machine learning and statistical modelling.
- Experience working with unstructured documents and extracting reliable information from complex text.
- Strong communication and collaboration skills, with the ability to work effectively with engineers, product teams, sales and sustainability experts.
- A customer-minded, proactive and innovative approach: you investigate problems, raise useful questions and bring practical ideas informed by customer and market needs.
- You use Claude as a daily working partner, not an occasional tool, to multiply your productivity across brainstorming, research, analysis, coding and testing.
You understand what it can and cannot do, validate its outputs, and remain accountable for the final work.
- Authorised to work in the United Kingdom.
- Experience with LLM applications or frameworks, including RAG, embeddings, vector databases, prompt engineering, evaluation or Open AI APIs.
- Experience in carbon accounting, sustainability reporting, ESG data, carbon markets, climate risk or environmental data quality.
- Exposure to geospatial data analysis, GIS or remote-sensing data.
- How you work
You will thrive here if you
- Are curious about both the technology and the real-world decision it supports.
- Can work through ambiguity, challenge assumptions constructively and remain pragmatic and delivery-focused.
- Take responsibility for quality, transparency and usability, especially where AI outputs inform sustainability or commercial decisions.
What we offer
- The opportunity to contribute to meaningful AI products in sustainability intelligence and carbon markets.
- Direct exposure to product strategy, clients and senior decision-making, with scope to grow across data science, AI and product.
- Flexible remote working, with occasional visits to our London office.
The process includes two interviews: a discussion of your experience and selected projects, followed by a product/problem-solving exercise.
Carbon AI is an equal-opportunity employer. We welcome applications from people with different backgrounds and perspectives.
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Data Scientist employer: CARBONAI LIMITED
At CarbonAI, we pride ourselves on being an excellent employer by fostering a collaborative and innovative work culture that empowers our Data Scientists to make a real impact in the field of sustainability. With flexible remote working arrangements and opportunities for professional growth, employees can engage directly with product strategy and client interactions, ensuring their contributions are meaningful and valued. Our commitment to diversity and inclusion further enriches our team dynamics, making CarbonAI a rewarding place to advance your career while contributing to a sustainable future.
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We think this is how you could land Data Scientist
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We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at CARBONAI LIMITED!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
