Wise
Financial Services
StaffDataScientist-AML
Neural analysis suggests this role is
optimal for mid candidates.
“Staff Data Scientist - AML at Wise. Skills: Machine Learning, AI systems, AML detection, Python, TensorFlow, PyTorch, LLMs. Lead the development and deployment of machine learning models. Design and build modular detection systems”
What You'll Achieve.
Develop our risk detection and assessment to the next level; Provide our customers with the seamless service they deserve; Build a globally scalable AML prevention and detection engine; Maintain Wise as a secure environment for our legitimate customers; Utilise machine learning techniques to identify potential risks; Meet the requirements set by regulators and auditors but also surpass their expectations; Enhance our AML detection capabilities; Ensure high-quality model outputs
Industry & Context.
What They're Looking For.
Must Have
5+ years in developing and deploying production-grade AI systems and Machine Learning (ML) in financial risk or fraud domains, Skilled in Python, Experience with big-data frameworks, Working with large scale databases
Nice to Have
GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, dbt Certified
What You'll Do.
Lead the development and deployment of machine learning models
Design and build modular detection systems
Conduct large-scale training and hyperparameter tuning
Define performance metrics
Design and implement strategies for data collection
Develop scalable deployment strategies
Integrate LLMs with AI agents
How You'll Work.
Team & Collaboration
Collaborate with cross-functional teams; Collaborate with Platform teams; Foster a partnership between AML investigators and the product team; Work independently in a cross-functional and cross-team environment
Communication Scope
Communicate complex data findings to non-technical stakeholders effectively; Able to adapt communication style to suit different audiences; Effectively engage and advise both technical and non-technical stakeholders with clarity and logic
Full Job Description
Wise is a global technology company, building the best way to move and manage the world’s money. Min fees. Max ease. Full speed. Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money. As part of our team, you will be helping us create an entirely new network for the world's money. For everyone, everywhere. More about [our mission](https://wise.jobs/our-mission) and [what we offer](https://wise.jobs/what-we-offer). We’re looking for aStaff Data Scientist to join our growing AML Team in Tallinn, Estonia. This role is a unique opportunity to work behind the scenes of company transactions, develop our risk detection and assessment to the next level regarding regional typology understanding and at the same time, provide our customers with the seamless service they deserve. What you build will have a direct impact on [Wise’s mission](https://www.transferwise.jobs/what-we-do/) and millions of our customers. About the Role: The AML team at Wise is dedicated to safeguarding our platform against financial crime, while ensuring seamless service for our legitimate customers. Leveraging cutting-edge machine learning, real-time transaction monitoring, and data analysis, our team is responsible for developing and enhancing AML detection systems which have evidenceable regional coverage of different financial crime typologies and red flags. Software engineers, data analysts, data scientists and compliance specialists collaborate on a daily basis to continuously improve our systems and provide support to our AML investigation team. Our vision is: * Build a globally scalable AML prevention and detection engine to maintain Wise as a secure environment for our legitimate customers. * Utilise machine learning techniques to identify potential risks associated with customer activity. * Foster a strong partnership between our AML investigators a
Applying for this Staff Data Scientist - AML role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on SmartRecruiters
- SmartRecruiters often includes a video screening step — check camera and mic permissions.
- Link your GitHub or portfolio directly in the profile section for technical roles.
- Applications may be reviewed by AI scoring before reaching a recruiter — use keywords from the job description.
ANONYMOUS · UNFILTERED
What do employees actually say about Wise?
Real rants from real employees. Read before you apply.