Senior Upstream Data Scientist: Materials & Emissions in London

Senior Upstream Data Scientist: Materials & Emissions in London

London Full-Time 60750 - 74250 £ / year (est.) On-site
Atmospheric AI

At a Glance

  • Tasks: Develop models to quantify carbon intensity and production pathways for raw materials.
  • Company: Atmospheric AI Limited, a leader in sustainable data science.
  • Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
  • Other info: Collaborative environment focused on innovation and sustainability.
  • Why this job: Make a real impact on sustainability while working with cutting-edge technology.
  • Qualifications: Experience in data science, Python, and geospatial data analysis.

The predicted salary is between 60750 - 74250 £ per year.

Atmospheric AI Limited is seeking a data scientist to develop upstream models and datasets that quantify carbon intensity and production pathways for raw materials.

You will work with Python, geospatial data, and production-grade tools to validate outputs and support decision making in supply chains.

The role emphasizes rigorous provenance, defensible methodology, and collaboration across data science and product teams in a London-based setup.

Senior Upstream Data Scientist: Materials & Emissions in London employer: Atmospheric AI

Atmospheric AI provides a collaborative work environment where employees can engage in meaningful projects that address critical environmental challenges. The company emphasizes professional growth and offers opportunities to work with innovative technologies in the field of data science. Employees are part of a team that contributes to impactful solutions in the materials economy.

Atmospheric AI

Contact Details:

Atmospheric AI Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Upstream Data Scientist: Materials & Emissions in London

✨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 Atmospheric AI!

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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 Senior Upstream Data Scientist: Materials & Emissions at Atmospheric AI.

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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 Atmospheric AI.

✨Apply Directly through Our Website

When you find a suitable opening like Senior Upstream Data Scientist: Materials & Emissions at Atmospheric AI, 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 Senior Upstream Data Scientist: Materials & Emissions in London

Data Science
Python
Geospatial Data Analysis
Model Development
Carbon Intensity Quantification
Production Pathways Analysis
Data Validation

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 Atmospheric AI, 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 Atmospheric AI. 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 Atmospheric AI

✨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 Atmospheric AI!

✨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.