Customer Support Area Lead

About the company 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 . The role 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 .

We are looking for a shift-based CS Operations Team Lead to join the Customer Support department. In this role, you will be responsible for the performance, engagement, and real-time execution of an in-house support team, while maintaining visibility over outsourced partner operations.

We are looking for a shift-based CS Operations Team Lead to join the Customer Support department. In this role, you will be responsible for the performance, engagement, and real-time execution of an in-house support team, while maintaining visibility over outsourced partner operations.

About the company 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 . The role We’re looking for a Data Science Lead to join our AML Risk team in Tallinn. This role is a unique opportunity to work on building out the lead Data Science team and machine learning based technical solutions in the AML Risk team, which owns AML detection across all of the Wise licenses. This is an exciting opportunity to develop the program in a global company. Your work will allow Wise to keep our customers safe and making sure we can keep our ecosystem free of bad actors in a scalable way. What you build will have a direct impact on Wise’s mission and millions of our customers . About the Role: In the Anti-Money Laundering (AML) Risk team we are developing systems which are a mixture of unsupervised and supervised learning, with GenAI to detect and mitigate Financial Crime on a global scale. You will be making sure the AML Risk Data Science team is well equipped and working on cutting-edge technology to sustainably support Wise’s growing customer, transaction and product space. You will be stepping into an already functioning, but growing product team. Here’s how you’ll be contributing: AML Risk Detection System Development Developing efficient and effective AML detection controls using a mixture of unsupervised, semi-supervised and supervised learning with GenAI Creating frameworks to prove controls coverage at a regional level Developing technologies to serve Wise’s diverse international user base Building a team of high performing specialists Working with product managers and engineering leads to understand staffing requirements Hiring specialists Mentoring more junior members of the team on technical and non-technical skillsets Performance Testing and Optimisation Evaluating our AML systems against internal and external benchmarks Developing decisioning layers to find optimal trade-offs between precision and recall Providing data-driven insights on potential outcomes under various scenarios Operational Process Development Collaborating with operational teams to refine processes, ensuring effective feedback integration into our automation systems Designing and managing projects that utilise excess operational capacity, such as manual data labelling for model improvement Creating systems which provide in-depth insight to investigators on red flags and typologies present on profiles/transactions Deployment and Implementation Packaging algorithms into deployable libraries/objects and transitioning them from staging to production environments Implementing and maintaining scheduled processes for data gathering and model retraining using automated pipelines Maintaining production-grade Python services Qualifications A bit about you: Experience implementing, training, testing and evaluating performance of Machine Learning systems; Strong Python knowledge. A big plus for proven familiarity and experience with OOP principles; Experience with statistical analysis, and ability to produce well-designed experiments; A strong product mindset with the ability to work independently in a cross-functional and cross-team environment; Good communication skills and ability to get the point across to non-technical individuals; Strong problem solving skills with the ability to help refine problem statements and figure out how to solve them. Some extra skills that are great (but not essential): Familiarity with automating operational processes via technical solutions, for example Large Language Models Willingness to get hands dirty with operational side by sides to understand their pain points Knowledge and experience within the Financial Crime domain 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 .