Contract with Client
IT & Telecom, Banking & Insurance
About this vacancy
Would you like to play with the latest technologies in a sizzling data environment, while building a fintech and a team from scratch and make the world a safer and better place at the same time?
We offer you a very cool technical playground with all the latest technologies you need to create and accelerate our innovative, state-of-the-art transaction monitoring platform. A must-have to create the most effective detection and new insights, that will help banks, public sector and law enforcement to collectively defeat financial crime.
A sneak preview on your new playing field:
- Building a bleeding edge, world-wide unique MLOps platform for massive amounts of data at a scale that is very, very rare
- A truly unique technical challenge
- Develop best-in-class model and data lineage solutions that make even complex ML pipelines meticulously reproducible
- Conceptualize and implement sophisticated model observability and controllability solutions
- Ensure scalability of Data Science efforts by developing our feature store
- Combine managed solutions, customizations and open source tools to help us build a platform that meets our special requirements
- Work together with AWS experts to push the boundaries of what’s out there
- Work together with Data Scientists in taking pipelines to production on our MLOps platform
Have a look at Transaction Monitoring Netherlands (TMNL). They are creating a top-notch detection and monitoring company to defeat financial crimes such as money laundering and the financing of terrorism. They are forming an energetic and inspired team, where the curious, talented minds in anti-money laundering (AML) and financial crime detection, data science, data engineering, advanced analytics and artificial intelligence join forces to make this possible. Together, they design, build, accelerate and execute the collective monitoring of money transaction data from the five largest Dutch banks to begin with. This way, they will be able to detect signals and patterns of financial crimes at an unprecedented level.
At TMNL you will experience the freshness, the freedom, the mandate and the pace forward of a start-up. They are based on a healthy growing ground, as they have the full dedication and support of the five largest Dutch banks from the start.
They offer you a very cool technical playground with all the latest technologies you need to create and accelerate our innovative, state-of-the-art transaction monitoring platform. A must-have to create the most effective detection and new insights, that will help banks, public sector and law enforcement to collectively defeat financial crime.
At TMNL, key values as responsibility to society, constant curiosity, courageous choices and learning and growing together are very important to us. Just like a strong fundament based on ethics, embrace all backgrounds, personalities and opinions, honesty and vulnerability in our interactions and constant experimentation. This way we will not only achieve the edge and quality in our work we aim for, but also the long-lasting societal change by finding and exposing the smartest bad actors in the financial world.
We’ll go all in to make sure you are not only excited about the purpose of your work but also about the work you do on a daily basis, who you work with and the culture you work in. Joining our team now, also means we invite you to contribute to co-creating the company you always wanted to work for.
As much as we love our work, we also enjoy a healthy work-life balance and an excellent benefit package. As a team, we will contribute all we can to make sure you are as happy, healthy and energetic at work as in life, so we can help each other to become better tomorrow then we are today.
- Experience with implementing or helping lift Data Science/Machine Learning to production
- AWS, Amazon SageMaker
- Apache Spark
- Experience with architecting complex, cloud-native (ideally AWS) software solutions having ML at its core
- Knowledge of / experience with MLOps principles and tools (model & data lineage, observability, feature stores, model registries…)
- Graph algorithms, graph query languages, graph databases
- AWS Glue
- CI/CD pipelines
- Experience in the financial industry