Staff Data Scientist - AML at Wise

Tallinn, Harju, Estonia -

Full Time

Start Date

Immediate

Expiry Date

15 Oct, 26

Salary

122000.0

Posted On

17 Jul, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Machine Learning, Deep Learning, TensorFlow, PyTorch, LLamaIndex, LangGraph, LLM Orchestration, Anomaly Detection, Graph-based Models, Neural Networks, Big Data Frameworks, Technical Leadership, Data Strategy, AML Detection, Financial Risk Analysis

Industry

Financial Services

Description

Company 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 and what we offer. Job Description We’re looking for a Staff 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 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 and the product team to develop solutions that leverage the expertise of AML investigation specialists. Not only meet the requirements set by regulators and auditors but also surpass their expectations. We are looking for a highly skilled Staff Data Scientist to lead technical innovation and drive the development of advanced data science solutions. This role is pivotal in enhancing our AML detection capabilities. Here’s how you’ll be contributing: Innovate and Develop: Lead the development and deployment of machine learning models, including neural networks, anomaly detection, graph-based models, Transformers. Design and build modular detection systems able to detect in an evidenceable way red flags and typologies across different regions where Wise operates. Lead and Collaborate: Mentor team members and promote adoption of AI workflows for automation across the business. Collaborate with cross-functional teams to integrate data science solutions into AML detection product offerings. Deploy and Integrate: Develop scalable deployment strategies together with Platform teams and integrate LLMs with AI agents for seamless production use Optimize and Evaluate: Conduct large-scale training and hyperparameter tuning, and define performance metrics to ensure high-quality model outputs. Data Strategy and Management: Design and implement strategies for data collection, curation, and augmentation to support robust model training. Documentation and Reporting: Communicate complex data findings to non-technical stakeholders effectively. Document the development and maintenance processes for models and features. Qualifications A bit about you: Demonstrated expertise (5+ years) in developing and deploying production-grade AI systems and Machine Learning (ML) in financial risk or fraud domains. Technical Proficiency: Skilled in Python, capable of delivering production-ready Python services as required; possesses hands-on experience with neural networks and deep learning models; has comprehensive knowledge of machine learning frameworks such as TensorFlow or PyTorch, as well as AI agent frameworks like LLamaIndex and LangGraph; well-versed in LLM orchestration and MCP usage. Data-driven mindset: skilled in designing data strategies, including data collection, curation, and augmentation, to support model development. Experience with big-data frameworks and working with large scale databases Technical leadership and mentorship: demonstrated ability to guide, mentor and level-up teams on technical aspects, fostering a collaborative and innovative work environment Excellent communication skills, capable of simplifying complex technical concepts for easy understanding; able to adapt communication style to suit different audiences; can effectively engage and advise both technical and non-technical stakeholders with clarity and logic A strong product mindset with the ability to work independently in a cross-functional and cross-team environment; Additional Information For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive. We're proud to have a truly international team, and we celebrate our differences. Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers. If you want to find out more about what it's like to work at Wise visit Wise.Jobs. Keep up to date with life at Wise by following us on LinkedIn and Instagram. Compensation: EUR 91500 - EUR 122000 - yearly

Responsibilities

Lead the development and deployment of advanced machine learning models and modular detection systems to identify financial crime typologies. Mentor team members and collaborate with cross-functional teams to integrate AI solutions into AML product offerings.