Carbon Analytics Engineer (Remote/Hybrid) in Cambridge

Carbon Analytics Engineer (Remote/Hybrid) in Cambridge

Cambridge Full-Time 45000 - 55000 £ / year (est.) Home office (partial)
Neutreeno

At a Glance

  • Tasks: Automate emissions insights and deliver scalable data pipelines for diverse industries.
  • Company: Neutreeno, a cutting-edge startup from the University of Cambridge.
  • Benefits: Flexible remote/hybrid work, competitive salary, and opportunities for professional growth.
  • Other info: Join a dynamic team in a fast-paced environment with great career potential.
  • Why this job: Make a real impact in sustainability while working with innovative technology.
  • Qualifications: Experience in data engineering and a passion for emissions science.

The predicted salary is between 45000 - 55000 £ per year.

Neutreeno, an emissions-to-performance platform born out of the University of Cambridge, seeks a Carbon Analysis Engineer to automate emissions insights for customers.

You’ll bridge emissions science and data engineering, delivering scalable pipelines across diverse industries, and supporting customer-facing storytelling.

You’ll join a fast-paced startup with a hybrid Cambridge-office setup, collaborating with data science, modelling and CS teams to ensure data quality and actionable insights.

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Carbon Analytics Engineer (Remote/Hybrid) in Cambridge employer: Neutreeno

At Neutreeno, we are not just a company; we are a movement towards a sustainable future. Our dynamic work culture fosters autonomy and collaboration, allowing you to thrive as an Enterprise Account Executive while making a tangible impact on global emissions reduction. With opportunities for personal and professional growth in a fast-paced startup environment, along with a hybrid work model that promotes flexibility, Neutreeno is the ideal place for those passionate about driving meaningful change.

Neutreeno

Contact Details:

Neutreeno Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Carbon Analytics Engineer (Remote/Hybrid) in Cambridge

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Neutreeno!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Carbon Analytics Engineer (Remote/Hybrid) at Neutreeno.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Neutreeno.

Apply Directly through Our Website

When you find a suitable opening like Carbon Analytics Engineer (Remote/Hybrid) at Neutreeno, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Carbon Analytics Engineer (Remote/Hybrid) in Cambridge

Data Engineering
Emissions Analysis
Automation Skills
Data Quality Assurance
Scalable Pipeline Development
Collaboration
Storytelling with Data

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!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Neutreeno, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Neutreeno. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Neutreeno

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!

Showcase Your Projects

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 Neutreeno!

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.