Qonto recrute un(e)

Machine Learning Engineer

CDI • Paris, France

Cette offre est lié au département Data science


Our mission? Creating the finance solution that energizes SMEs and freelancers, so they can achieve more(e)We simplify everything from everyday banking to bookkeeping and spend management(e)At Qonto, we’re passionate about creating the best product - with both impact and a great user experience(e)So if you’re looking for an ambitious team that’s revolutionizing a rather old-fashioned industry, get in touch(e)You can find out more about the Qonto Way here.

Alexandre and Steve launched Qonto in July 2017(e)Since then, the team has made great strides:
- Becoming market leader for online SME banking in Europe with 250,000 SME clients
- Getting recognized as one of the Top 10 startups to work for (LinkedIn | Glassdoor)
- Opening offices in Paris, Berlin, Milan, and Barcelona
- 700+ happy Qontoers building a finance solution businesses love to use.

Our values:
Ambition | We tackle big challenges(e)No matter what
Teamwork | We create momentum by working together, at the same speed
Mastery | We pursue excellence through continuous learning(e)We face challenges with humility(e)Every day
Integrity | We're open(e)We're honest(e)And we earn the trust of our clients and each other

To follow Qonto's ambition, we created the Data Department, handling Data Analysis, Engineering, and Science. The data department has since grown from 5 to 35+ people within two years (and we're still hiring)!

Within the Data department, the Data Products Team (10+) is an applied machine learning (ML) team with a focus on delivery, working closely with our data engineering teams that build data pipelines & manage data warehouses.

As a Machine Learning Engineer, you will be collaborating closely with Simon, our Senior Lead Data Product within our subteam in charge of fraud detection and risk scoring models at Qonto(e)

The Machine Learning systems you’ll release will interact with every transaction within our payment institution: this is one of the most challenging and high-impact machine learning issue in our sector as a FinTech company.

🤝 Your future manager

Your manager will be Simon, who is in charge of the Data Products team at Qonto!

His background? After his experience in fast-scaling organizations at both ManoMano & Kapten where he managed and built Data Science teams from scratch, Simon joined Qonto to structure our Data Products departments!

What does he bring to the team? As an expert in his field, he has hands-on experience on implementing and taking Machine Learning models into production in product-driven & cross-functional teams(e)Simon also has a true passion for mentoring and coaching the team..

👩‍💻🧑‍💻 As a Machine Learning Engineer at Qonto, you will

• Own the Machine Learning lifecycle, from experimentation and prototyping to deployment into production pipelines
Investigate and fix production issues from data products your team owns
Work hand-in-hand with Fraud, Risk & Compliance stakeholders
Ensure high quality by establishing and using the best engineering practices
Design, build, test, document, run, review and maintain production code in Python
Support a critical service used by tens of thousands of users on a daily basis

🤔 What you can expect

• The opportunity to build from scratch challenging machine learning systems that are crucial for Qonto’s future.
The Data Products team was funded in mid-March 2022(e)You’ll be at the forefront of this new effort and contribute to building new machine learning systems for business needs that aren’t yet answered(e)You won’t be optimizing a fleet of previously developed models: rather, you’ll have the opportunity to write the next chapter from the ground up.

• Qonto is highly data-driven and our different business stakeholders are also thriving in that direction.
Our stakeholders have a strong business experience in Fraud, Risk, and Compliance, but also understand what Machine Learning is(e)For instance, Arnaud (Head of Risk) is a former Data Scientist(e)You’ll work with stakeholders than can challenge you and speak the same language.

• Qonto has a culture based on efficient feedback loops that allow us to understand & monitor quickly the impact of our actions.
The Qonto Way, a set of values inspired by the Lean Methodology, stresses quality(e)You’ll work on one topic at a time (one piece flow), with a culture that promotes right-first-time and mastery.

• Our data teams are part of our Tech team, granting us easy access to our infrastructures while also supporting strong teamwork.
The Data Products team reports to Jérémie (VP Data), who works with Aymeric (CTO)(e)The Data Products team is a Tech team: it’s held to the same software engineering standards as our front or backend engineers, and benefits from the strong support of the SRE team(e)The team owns its services in production and deploys them on the same infrastructure as the rest of the Tech team (AWS, Argo CD, Kubernetes).

• The team is at the heart of Qonto’s business with a powerful impact on our bottomline.
The Data Products team drives business impact at the core of Qonto(e)As a payment institution, fighting fraud is both a requirement to operate and a prerequisite to thrive(e)What we do has a direct effect on the company and is an enabler for scaling(e)You’ll work on difficult problems (few or no labeled data, imbalanced datasets, adversarial setting, concept drift) where the outcome matters.

🏅 About You

User-focused and outcome-oriented: You want to solve high-impact business problems and deliver value to our users in production
Communication skills: You have effective communication skills, to build alignment and articulate purpose(e)As a remote-first team, good writing is key
Mastery: You have strong technical experience building real-time ML models for production(e)You care about the craft and champion high standards
Language: You are fluent in English.

If you read this far and feel like this could be a great opportunity for you, don't let the imposter syndrome prevent you from applying and hit the button "Apply", we'd really love to hear from you!
🎁 Perks
A laptop(e)An inclusive work environment(e)A tailor-made career track(e)And so much more to help you succeed…

Office & Team Life
- A fully-renovated building in the center of Paris with WeWork services
- The latest equipment from Apple
- Monthly team events
- Free coffee and snacks in the kitchen

All our benefits
- A competitive salary package
- Remote Policy: from 2 days per week to Full remote
- 5 to 10 days off in addition to the legal 25 days
- Alan health insurance, Moka Care to take care of your mental health, andGymlib for sports and wellness activities
- Swile Card for lunch
- An inclusive environment with a focus on parity: 40% of our teams are women
- A progressive parenthood policy as part of our commitment to the Parental Act (1 in 6 of Qonto employees is a parent!) and childcare benefits with selected partners
- Relocation package and visa sponsorship for international talents (we have 50+ nationalities) including access to Busuu to improve your language skills
- Career tracks and mobility opportunities that can match all expectations

💪 Our hiring process:

- A 60 min video call with one of our Talent Acquisition Managers, to better understand your career plan and answer any questions you may have
- A 60 min video call with your future manager, to be aligned on expectations on both sides and to talk about how you would work together
- A remote exercise to evaluate your skills and give you a taste of what working Qonto could be like
- Video calls or onsite interviews with future team members (optional) to help you understand what working at Qonto is like
- A final video call or onsite interview with the manager of your future Department

Check this article to learn more about the hiring process and we will send you an interview guide so you can best prepare yourself.
On average our process lasts 20 working days and offers usually follow within 48 hours 🤞


Thank you for considering joining Qonto(e)We cannot wait to learn more about you!
If you want to learn more about us: Les Echos | Qonto's Blog | LeFigaro | TechCrunch

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