Lead Data Scientist

About the role

You will define and own the end-to-end lifecycle of machine learning models used in KYC document verification, taking full responsibility for turning complex risk and identity challenges into robust data products. This role sits at the critical intersection of regulatory risk decision-making and customer experience, where your analytical judgment directly influences how safely and smoothly customers join and use Wise. You will partner with compliance, product, and engineering teams to translate ambiguous business problems into clearly defined data science initiatives that can be executed and scaled. Your work will shape both the integrity of KYC checks and the clarity of information presented to customers during onboarding. You will own not only the modeling but also the strategic data thinking that determines what evidence is gathered and how it is evaluated. Your contributions will support millions of customers worldwide by enabling fast, fair, and secure onboarding flows. You will be expected to question assumptions, probe edge cases, and design experiments that reveal the true behavior of models in production.

Key facts

What you will do

• Partner with integrated teams to plan and scope data science initiatives for KYC workflows, aligning objectives with risk, compliance, and product goals.
• Discover and propose machine learning opportunities that reduce risk, improve verification outcomes, and enhance the customer experience across global onboarding journeys.
• Communicate the value, constraints, and impact of data science projects to both technical and non-technical audiences, ensuring clarity on trade-offs and assumptions.
• Manage the full lifecycle of models used in document verification, from data preparation and feature engineering through training, evaluation, deployment, and ongoing monitoring.
• Build and curate large image and tabular datasets, ensuring traceable data lineage, proper labeling standards, and strict adherence to regulatory compliance.
• Develop and refine deep learning models for document image analysis, balancing accuracy, latency, and robustness under strict compliance requirements.
• Track model performance in production by implementing rigorous metrics, alerts, and dashboards that monitor drift, data quality, and system reliability.
• Mentor junior data scientists and engineers, fostering adherence to industry standards, best practices, and a culture of rigorous experimentation within the team.
• Explore document verification research and emerging methodologies to identify approaches that help prevent fraud, forgery, and criminal activity.
• Keep pace with advances in machine learning and rapidly translate new ideas into production-ready systems that meet the needs of a global regulated business.

Requirements

• Proven ability to coordinate model lifecycles across intake, development, review, and deployment, ensuring accountability at each stage.
• Experience managing large-scale image and structured datasets for high-stakes verification tasks, with awareness of data quality and bias implications.
• Hands-on experience iterating on deep learning image models and measuring performance rigorously using appropriate validation strategies.
• Strong Python engineering skills, with clean, maintainable code aligned with industry best practices, version control, and reproducible workflows.
• Commitment to continuous learning, adapting research insights, and integrating new methodologies into real-world production environments.
• Demonstrated skill in articulating trade-offs, model behavior, and performance metrics to diverse stakeholders with varying levels of technical background.
• Track record of mentoring and guiding junior colleagues in data science and engineering practices, helping them grow their technical and professional skills.
• Understanding of compliance and risk considerations in financial services, and experience working within regulated, high-compliance environments.

Nice to have

No specific formal qualifications are required; demonstrated experience and clear communication are prioritized.

Skills and tools

• Python for data engineering and model development, including scripting, automation, and integration with production systems.
• Deep learning frameworks for image and tabular modeling, with familiarity with modern architectures and training workflows.
• Data versioning, monitoring, and dashboarding tools to track experiments, model behavior, and business metrics over time.
• Experience in regulated, high-compliance environments, with awareness of operational, legal, and governance constraints.
• Familiarity with MLOps practices, including model packaging, deployment pipelines, and collaboration with engineering teams.
• Exposure to identity verification workflows, document fraud patterns, and techniques used to detect synthetic or manipulated media.
• Ability to work asynchronously and collaboratively across distributed teams, using clear documentation and structured communication.
• Curiosity about global financial behavior and motivation to build systems that support inclusive access to money movement.

Practical notes

Please note that employment details, including compensation, are subject to final verification and policy rules. Only candidates who meet the outlined requirements and demonstrate alignment with the responsibilities will be considered for progression in the hiring process.

Diversity and inclusion

We believe diverse teams build better products. We encourage applications from all backgrounds and under-represented groups. Wise is committed to building an inclusive culture where every team member feels respected and empowered.

Life at Wise

Wise is a global technology company enabling fast, low-fee international money movement. You will help create a new network for the world's money, with transparency, fairness, and simplicity at its core.

Learn more about Wise's mission, values, and benefits on Wise.Jobs. Follow Wise on LinkedIn and Instagram to stay updated on company life and culture.

What you'll do

Wise is a global technology company, building the best way to move and manage the world's money. Min fees. Max ease.