The fashion industry is responsible for 5-10% of global greenhouse gas emissions (GHG). More and more companies are using Carbon Management Platforms to measure and create CO2 reduction plans. However, most of these generalist solutions are not tailored for a fashion brand, which requires detailed insights on materials and manufacturing processes throughout the entire lifecycle of its products.

This is why we built Carbonfact, the leading Carbon Management Platform for the textile and fashion industry. Our platform automates life cycle assessment (LCA) at the product level, enabling brands to gain a high-resolution understanding of their Scope 3 emissions and model out product-level changes on the company’s broader environmental trajectory.

We raised a total of $17 million from Alven, Headline, Y Combinator and angel investors. Now, hundreds of brands and fashion groups are using Carbonfact (e.g. New Balance, Carhartt, Allbirds, Adore Me, Armedangels, Fusalp, Allbirds, Happy Socks, etc.).

Data at Carbonfact

You can’t reduce what you can’t measure: many fashion brands want to make changes, but they don’t have the figures to make informed decisions. They have data: bill of materials, product catalogs, purchase orders, etc. But more often than not, the real-world data is messy and incomplete.

Data Scientists at Carbonfact work hand in hand with customers to measure the environmental impact of their products. We do this mainly by writing code that processes the customer's data, sends it to our LCA engine and analytics engineering layer, and surfaces the insights to our product platform.

The data we get to work with is fascinating: clothing items, factories, shipments, energy usage, environmental footprints. It’s heaven if you’re looking to work on a meaningful data science topic!

We work closely together with our Customer Success, Engineering and Science teams to deliver a robust product platform and ensure stellar customer experiences.

As a Data team, we write production-grade code, use the modern data stack, leverage exciting new technology when it makes sense, and even open source some of our code. We make things scalable while keeping the tech as simple as possible.

What we’re looking for

We’re looking for full stack data scientists: people who enjoy working with data on all stages, from messy data processing to dashboard creation. We believe data scientists who are empowered to own projects from A to Z can have tremendous impact. It also makes our jobs so interesting and rewarding – we see that the work we do puts smiles on the faces of our customers!

Your responsibilities include:

• Parse, normalize and convert raw business data into internal data models. 
• Build analytics on customer data for internal consumption and external presentation.
• Collaborate with Customer Success, Engineer and Science teams.

• You have applied Python skills. Our internal parsing toolbox is written in Python, and expect you to make it better, not just to use it. 
• You have basic NLP experience (regex, typo handling, normalization, etc.)
• You have SQL skills and take interest in the analytics engineering ecosystem 
• You have basic software engineering skills (clean code, unit tests, version control). Here clean code matters a lot, because it’s directly affecting our customers. 
• You communicate well in English. You’ll be facing customers on a regular basis, discussing technical concepts in English. English is also the main language we communicate with internally.
• You got a knack for working with heterogeneous, real-world data. 
• Bonus if you have experience in data engineering.

☝️ We recruit great people, not only to fill roles. If this sounds like the kind of person you can and want to grow into, then please feel welcome to apply. For instance, our Head of Data Max wasn’t very customer-oriented at first, and he developed this competency with time.

Work environment

• You can read more about our 5 principles here.
• You get to work and learn with awesome colleagues: Max, Félix, Gaëlle
• You can work remotely, as long as you’re based in Europe.
• We pay for co-working spaces up to 300€/month if your position is remote.
• We cover the usual modern amenities (MacBook, headset, ChatGPT subscription, Github Copilot, etc.)
• We'll cover 100% of your health insurance with Alan at the best coverage level
• We have an office in the 10th arrondissement of Paris, where you’re welcome to join!
• We organize work retreats 3 times a year.
• We determine the compensation package (salary + equity) based on an internal grid which is fully transparent. At the time of hiring, we’ll determine your level based on the position, your track-record and experience. You will then be promoted to higher levels based on your performance and your impact on the company. Each level is associated with a predetermined compensation.
• For this position, we are looking for candidates with 3+ years of experience. You can expect a salary between €60k and €90k depending on levels. You can also expect significant equity with employee-friendly exercise rights.

Application and interview process

Please submit your application on our careers page. If there is a fit, we will share some availability to do a 30-minute exploratory call with the hiring manager.

If the exploratory call goes well, these are the following steps:

1. 1 hour live data modeling test
2. A data parsing take-home task, with a 1 hour max live restitution
3. 1 hour live analytics test
4. Principles fit with a Carbonfact co-founder
5. Reference calls