Staff Data Scientist

About the role

We are seeking a talented individual to join our Anti-Money Laundering (AML) team in Tallinn, Estonia. In this position, you will be instrumental in developing sophisticated systems designed to safeguard our platform against financial crimes. Your expertise will guide the technical strategy for detecting regional risks, ensuring that our services not only remain secure but also provide a seamless experience for our diverse global clientele.

Key facts

What you'll do

• Design and implement innovative machine learning models, including but not limited to neural networks, anomaly detection systems, graph-based models, and Transformers, to enhance our fraud detection capabilities.
• Develop modular detection frameworks that effectively identify and respond to regional financial crime indicators, adapting to evolving threats.
• Provide mentorship to team members, fostering a culture of knowledge sharing and promoting the adoption of automated AI workflows throughout the organization.
• Collaborate with cross-functional platform teams to deploy scalable solutions, integrating large language models (LLMs) with AI-driven agents for enhanced functionality.
• Oversee the training of large-scale models, including hyperparameter tuning and performance assessment to ensure optimal results.
• Formulate comprehensive data strategies that encompass data collection, curation, and augmentation to support model development and deployment.
• Communicate complex data insights and findings to non-technical stakeholders, ensuring clarity and understanding while maintaining thorough documentation of model lifecycles.
• Stay abreast of industry trends and advancements in machine learning and financial crime detection, applying this knowledge to continuously improve our systems.
• Engage in code reviews and contribute to the development of best practices within the team to maintain high standards of code quality and performance.
• Participate in strategic discussions regarding the future direction of the AML team and contribute to the overall vision of Wise.
• Analyze and interpret data to identify patterns and trends that can inform decision-making and enhance our risk management strategies.

Requirements

• At least 5 years of experience in developing and deploying production-level AI and machine learning systems, particularly within fraud detection or financial risk contexts.
• Strong proficiency in Python, with a demonstrated ability to create production-ready services that meet business needs.
• Practical experience with deep learning techniques and neural network architectures, showcasing a solid understanding of their applications.
• Familiarity with machine learning frameworks, specifically PyTorch and TensorFlow, to build and optimize models effectively.
• Experience working with AI agent frameworks, such as LangGraph and LLamaIndex, to enhance model capabilities.
• Understanding of LLM orchestration and the use of Model Control Protocol (MCP) for managing AI workflows.
• Background in big-data frameworks and experience in managing large-scale databases to support data-intensive applications.
• Proven leadership skills, with the ability to guide technical teams, mentor peers, and convey complex concepts to varied audiences in an accessible manner.
• Excellent problem-solving abilities, with a focus on innovative solutions to complex challenges in the financial sector.

Nice to have

• Experience with cloud-based services and deployment strategies for machine learning applications.
• Familiarity with regulatory requirements and compliance standards related to anti-money laundering and financial crime prevention.
• Knowledge of data visualization tools and techniques to effectively present findings and insights.
• Contributions to open-source projects or publications in relevant fields, showcasing thought leadership and expertise.
• Understanding of ethical considerations in AI and machine learning, particularly in the context of financial services.

Skills & tools

• Python
• TensorFlow
• PyTorch
• LLamaIndex
• LangGraph
• Neural Networks
• Transformers
• Anomaly Detection
• Graph-based models
• LLM orchestration
• MCP
• Big-data frameworks

Practical notes

This position is based in Tallinn, Estonia, and is a full-time role. The salary for this position will be competitive and commensurate with experience. We are open to considering candidates who require visa sponsorship to work in Estonia. If you are passionate about leveraging data science to combat financial crime and want to make a significant impact in a dynamic environment, we encourage you to apply. Join us at Wise and be part of a team that is dedicated to making financial services more secure and accessible for everyone.