Senior Machine Learning Scientist

4 Months ago • 8 Years +

Job Summary

Job Description

Adyen seeks a Senior Machine Learning Scientist with 8+ years of experience to design, implement, and deploy production-ready ML solutions, including AML systems, anomaly detection, and graph analysis. Must have expertise in big data frameworks, machine learning lifecycle, and statistical inference.
Must have:
  • Machine Learning
  • Big Data
  • Statistical Inference
  • ML Lifecycle
Good to have:
  • Graph Techniques
  • Bayesian Approaches
  • MLOps Frameworks
  • Airflow
Perks:
  • Own Your Career
  • Unique Challenges

Job Details

This is Adyen

Adyen provides payments, data, and financial products in a single solution for customers like Facebook, 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. The people of Adyen 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: Anti-Money Laundering (AML) systems, real-time anomaly detection based on time-series modeling, 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 and representation learning for behavior prediction and monitoring;
  • 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 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. Familiarity with graph-based techniques and Bayesian approaches is considered a plus;
  • You have strong familiarity with the standard data science toolkit, such as (py)spark, (Trino) SQL, Scikit-Learn, 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 are proactively taking 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.

 

Data positions at Adyen

We know companies handle different definitions for their data-related positions, this is for instance dependent on the size of a company. Since the birth of the Data Solution and the growth of all data streams, we categorized and defined all our positions. Have a look at this blogpost to find out! 

 

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.

Please, note that this role is a full-time position in Amsterdam. It will require a relocation in case you live outside of the Netherlands.

 

 

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