Data Scientist

Data Scientist (Associate) 

About Us 

Climate X is a purpose-driven climate adaptation data company set to revolutionise how the world manages assets, property, and infrastructure.  

We apply cutting-edge, peer-reviewed science to help prevent the worst impacts of climate change. We combine climate projections, remote sensing observations, and modelling to project the frequency and severity of physical climate risks such as floods, subsidence, storms, etc. 

Our SaaS platform lets financial institutions and real estate firms look at future climate pathways to:  

• help identify how property/company assets could be damaged by severe weather events and 

• what that damage might do to the asset valuations.  

• become more resilient to climate change and make smarter investment and lending decisions. 

 

The impact you’ll own 

As a Data Scientist at Climate X, you will join an interdisciplinary team of other Data Scientists, Climate Scientists and Geospatial experts, collaborating closely with our Engineering and Product teams to deliver impactful products to our clients.  

This role will support our NLP model, a core product within the business. This will involve developing an existing code base, research time for exploring new techniques and algorithms, fine-tuning LLM models on domain-specific datasets to enhance the performance of our existing model, perform statistical analysis and techniques for model evaluation, analyse text data to extract meaningful insights and trends and create visualizations to communicate findings and facilitate understanding of the model across the business and our clients. 

Essential Skills 

• Experience in a commercial Data Science role with strong understanding of machine learning algorithms and techniques (e.g., regression, classification, clustering), using ML packages in Python (such as sklearn, spaCy, NumPy, SciPy or others). 

• Experience with version control systems like Git for managing code changes and collaborating with team members. Knowledge of CI/CD pipelines (e.g. GitHub Actions) is a plus. 

• Experience with data visualisation tools and libraries (e.g., Matplotlib, Seaborn, Tableau, Power BI). 

• Experience with cloud services (e.g., AWS, Google Cloud Platform, Azure) for data storage and processing. 

• Ability to work with cross-functional teams using strong problem-solving skills and share insights to diverse audiences. 

 

Nice to have 

• Experience with web scraping using Python (such as BeautifulSoup, Scrapy, Selenium, Requests or others) is a plus. 

• Exposure to MLOps frameworks (such as MLFlow, Weights and Biases). 

• Knowledge of the financial services or real estate domain from a climate risk perspective, to inform a basic understanding of where data science is being applied, allowing for better context and interpretation of results. 

• Experience with processing and analysing geospatial data using Python (geopandas, GDAL, etc.) and/or other GIS software (such as QGIS) is a plus. 

Benefits 

🌍 Contribute to a business making purposeful impact related to climate change 

💡 Monthly training & conference budget to help you upskill and develop your career (£1,000 per year) 

📈 6 monthly appraisals and 12 monthly pay reviews 

💰 Pension contribution scheme 

🏡 Flexible hours and hybrid working (3 days/week in office; core hours 10am-4pm) 

🏥 Mental Health and Wellbeing support via Oliva  

🏖 25 days holiday, plus Bank Holidays, annual 3-day Christmas-closure, and half day on your birthday (36.5 days total!) 

🏏 Optional quarterly socials, dinners, and fun nights out 

🥐 A fully stocked supply of snacks, fruit, and refreshments for the days when you are in the office 

 

Equal Opportunities 

Climate X are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We are committed to creating an inclusive environment for all employees and welcome applications from individuals of all backgrounds.