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- Tasks: Join our team to develop and enhance machine learning models for climate risk analysis.
- Company: Climate X is a purpose-driven company tackling climate change through innovative data solutions.
- Benefits: Enjoy flexible hours, hybrid work, training budgets, and a dog-friendly office culture.
- Why this job: Make a real impact on climate adaptation while collaborating with diverse experts in a fun environment.
- Qualifications: Experience in data science, ML algorithms, Python, and cloud services is essential.
- Other info: We value diversity and are committed to creating an inclusive workplace for all.
The predicted salary is between 48000 - 72000 £ per year.
Senior Data Scientist/Machine Learning Engineer
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.
We advocate diversity with our founders, team, and investors from various backgrounds.
We’re not building just a team but a place of innovation where problem solving, and fun coexist to address the most significant challenge our society is facing now.
The impact you’ll own
As a Senior 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 product focused Data Science role with previous experience building end-to-end machine learning models.
- Strong experience with ML 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
Cycle to work scheme via gogeta
Enhanced maternity and paternity
Pawternity
Dog friendly office (official residence of Alfie, Chief Mischief Officer)
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.
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Senior Machine Learning Engineer employer: Climate X
Contact Detail:
Climate X Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Familiarize yourself with the specific machine learning algorithms and techniques mentioned in the job description, such as regression, classification, and clustering. Being able to discuss these in detail during your interview will show that you have the technical expertise needed for the role.
✨Tip Number 2
Highlight any experience you have with NLP models and how you've fine-tuned them in previous projects. This is a core aspect of the role, so demonstrating your hands-on experience will set you apart from other candidates.
✨Tip Number 3
Showcase your ability to work collaboratively with cross-functional teams. Prepare examples of past projects where you successfully communicated insights to diverse audiences, as this is crucial for the interdisciplinary nature of the position.
✨Tip Number 4
If you have experience with cloud services like AWS or Google Cloud Platform, be ready to discuss how you've utilized these tools for data storage and processing. This knowledge is essential for the role and will demonstrate your readiness to contribute immediately.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Understand the Company Mission: Before applying, take some time to understand Climate X's mission and values. Highlight how your skills and experiences align with their purpose-driven approach to climate adaptation.
Tailor Your CV: Make sure your CV reflects your experience in building end-to-end machine learning models and your proficiency with relevant ML algorithms and tools. Use specific examples that demonstrate your impact in previous roles.
Craft a Compelling Cover Letter: In your cover letter, express your passion for climate change and data science. Discuss how your background in NLP and collaboration with cross-functional teams can contribute to Climate X's goals.
Showcase Relevant Projects: If you have worked on projects related to climate risk, NLP, or data visualization, be sure to include them in your application. Provide links to your GitHub or portfolio to showcase your work.
How to prepare for a job interview at Climate X
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning algorithms and techniques. Highlight specific projects where you've built end-to-end models, and be ready to explain the tools you used, such as Python libraries like sklearn or spaCy.
✨Demonstrate Problem-Solving Abilities
Climate X values strong problem-solving skills. Prepare examples of how you've tackled complex data challenges in the past, especially in a product-focused environment. This will show your ability to contribute to their interdisciplinary team.
✨Familiarize Yourself with Climate Risks
Since the role involves climate adaptation data, having a basic understanding of climate risks and their impact on financial services or real estate will be beneficial. Research recent trends and case studies to discuss during the interview.
✨Prepare for Collaborative Discussions
As you'll be working closely with cross-functional teams, practice articulating your insights clearly to diverse audiences. Think about how you can communicate complex technical concepts in an accessible way, which is crucial for collaboration at Climate X.
