Senior Machine Learning Scientist

Posted 3 Days Ago
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Amsterdam
Hybrid
Senior level
Fintech • Payments • Financial Services
Adyen is the financial technology platform of choice for leading companies across the globe.
The Role
The Senior Machine Learning Scientist at Adyen will design, implement, and deploy machine learning algorithms, develop analytical pipelines, and automate experiments. They will collaborate with MLOps, iterate on state-of-the-art algorithms, and stay updated with industry research, while leading projects and communicating outcomes effectively across stakeholders.
Summary Generated by Built In

This is Adyen

Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition. 

For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster.

Senior Machine Learning Scientist

Adyen is looking for a Senior Machine Learning Scientist to join our team in Amsterdam, a person sitting at the cornerstone of algorithms, mathematics, and engineering, who can solve problems by designing and implementing production-ready machine learning solutions. You will be responsible for building, developing and deploying algorithms that power data products at Adyen. 

In this role, you will: 

  • Research, design, implement, train, deploy and monitor machine learning algorithms, either for batch prediction or real-time. Examples are:on-line learning algorithms to pick the best optimization decision in a changing environment, clustering algorithms to group customers/shoppers, supervised and semi-supervised learning methods for inference on risk patterns or graph analysis, representation learning for behavior prediction and monitoring, Anti-Money Laundering (AML) systems and real-time anomaly detection based on time-series modeling;
  • Develop orchestrated pipelines for analytical purposes and machine learning training;
  • Contribute to ongoing automation efforts for our experiments, training runs, validation runs and monitoring before, during and after deployment. Furthermore, collaborate with MLOps to improve our machine learning tooling;
  • Create and iterate on state of the art machine learning algorithms with both merchant and product audiences;
  • Stay up-to-date with the latest research and developments in the machine learning field, and apply this where applicable.

Who You Are:

  • You have 8+ years of experience as a machine learning or data scientist;
  • You have experience with the full machine learning model lifecycle in production flows;
  • You have experience with building and deploying Deep Learning models; 
  • You have experience leveraging a big data framework to create the pipelines needed to feed the models with appropriate data;
  • You have a good understanding of software engineering practices as well as data engineering and MLOps principles;
  • You have knowledge of data science and statistics and machine learning techniques. These include a strong grounding in statistical inference, machine learning for prediction, and causal inference. Experience with Deep Learning is a must have.;
  • You have strong familiarity with the standard data science toolkit, such as (py)spark, (Trino) SQL, Tensorflow, PyTorch, XGBoost/LightGBM, Pandas, MLFlow or similar MLOps frameworks, and Airflow;
  • You have an experimental mindset with a launch fast and iterate mentality. Extensive experience with designing and running experiments is essential;
  • You proactively take the lead in projects, from ideation to deployment. You have experience working with a wide range of stakeholders and can clearly communicate complex outcomes over a wide range of audiences.

Our Diversity, Equity and Inclusion commitments 

Our unique approach is a product of our diverse perspectives. This diversity of backgrounds and cultures is essential in helping us maintain our momentum. Our business and technical challenges are unique, and we need as many different voices as possible to join us in solving them - voices like yours. No matter who you are or where you’re from, we welcome you to be your true self at Adyen. 

Studies show that women and members of underrepresented communities apply for jobs only if they meet 100% of the qualifications. Does this sound like you? If so, Adyen encourages you to reconsider and apply. We look forward to your application!

What’s next?

Ensuring a smooth and enjoyable candidate experience is critical for us. We aim to get back to you regarding your application within 5 business days. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don’t be afraid to let us know if you need more flexibility.

This role is based out of our Amsterdam office. We are an office-first company and value in-person collaboration; we do not offer remote-only roles.


Top Skills

Deep Learning
Machine Learning

What the Team is Saying

Isabelle
Sebastian
Angel
Mika
The Company
HQ: Amsterdam
4,196 Employees
Hybrid Workplace
Year Founded: 2006

What We Do

By providing end-to-end payments capabilities, data-driven insights, and financial products in a single solution, Adyen helps businesses achieve their ambitions faster.

Our team members are motivated individuals from different cultures that help each other do remarkable things every day and across time zones. We face unique technical challenges at scale and we solve those as a team. And together, we deliver innovative and ethical solutions for businesses all across the world.

With 28 offices across the globe, Adyen serves customers including Meta, Uber, Spotify, Casper, Bonobos and L'Oreal.

Why Work With Us

At Adyen, everything we do is engineered for ambition. We started with payments, at a time when providers offered services based on a patchwork of systems built on outdated infrastructure. Ambition demanded more. So we set off to build a financial technology platform for the modern era, entirely in-house, from the ground up.

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Adyen Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Typical time on-site: Flexible
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