Director of Data Science - Fincrime

Posted 12 Days Ago
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London, Greater London, England, GBR
Hybrid
Expert/Leader
Fintech • Mobile • Payments • Software • Financial Services
Wise is one of the fastest growing fintechs in the world and we’re on a mission to make money without borders a new norm
The Role
Lead the Data Science team focusing on Financial Crime, providing technical leadership and innovation in AI and ML to optimize detection systems and safeguard users.
Summary Generated by Built In
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 visionary Director of Data Science to lead our Financial Crime team across our key hubs in London and Tallinn.

This is a pivotal role for Wise, offering a unique opportunity to delve deep into the intricate world of financial transactions, understanding the sophisticated mechanisms we employ to detect and prevent Financial Crime. 

As the Director of Data Science, you will provide technical leadership and mentorship to a highly skilled team of (25) data scientists, tackling complex, global-scale challenges inherent in the fight against Financial Crime. 

FinCrime at Wise is made up of 5 Squads: Fraud, Anti-Money Laundering, Onboarding & KYC, Screening and Funds & AUP. You’ll be an instrumental figure in safeguarding our platform and customers, ensuring robust risk mitigation while simultaneously delivering the seamless, trustworthy service our users expect.

Your expertise will shape the strategic direction and drive the adoption of cutting-edge artificial intelligence (AI) and machine learning (ML) technologies. These innovations will be crucial in building advanced Financial Crime detection and prevention systems, ensuring the secure and uninterrupted financial services our customers rely on. 

What you and your team build will have a direct impact on Wise’s mission and millions of our customers worldwide.

WHAT YOU’LL DO

  • Cross-Functional Collaboration & Customer Impact: Partner strategically with Product, Engineering, and Operations leaders, as well as Privacy and Compliance teams, to embed data science effectively into product roadmaps. This includes ensuring our solutions maximise customer and business value while rigorously addressing compliance and privacy requirements, with a strong focus on tangible customer solutions and measurable impact.

  • Technical Leadership & Innovation: Define and drive the technical vision for our FinCrime Data Science team, encompassing comprehensive data strategies, large-scale model optimisation, and the adoption of next-generation AI/ML architectures (e.g., transformers, agentic AI, computer vision). Shape the research agenda, evaluate emerging technologies, and foster a culture of experimentation and continuous learning to ensure cutting-edge solutions and maintain technical standards, model governance, and best practices.

  • Delivery Excellence & Operationalisation: Establish and oversee scalable deployment strategies, robust MLOps practices, model monitoring, A/B testing, and performance tracking to ensure production success. Drive process improvements that accelerate iteration speed and delivery quality across all data science projects.

  • Team Development & Mentorship: Lead, mentor, and grow our talented data scientists, building technical capabilities across the team, fostering career development, and promoting knowledge sharing on cutting-edge technologies and methodologies.

Qualifications

WHAT YOU’LL BRING

  • Proven Leadership & Team Development: 10+ years of experience leading high-performing data science teams, driving the development of production-grade Machine Learning and AI systems at scale, and delivering measurable business outcomes. Demonstrated ability to build, scale, mentor, hire, and grow both individual data scientists and data science leaders. This includes understanding the unique challenges and development paths for individual contributors versus those in leadership roles, and fostering collaborative and innovative team cultures, even when direct reports are also leading their own teams.

  • Deep Technical &  AI/ML Expertise: Strong technical foundation with expertise in coding (Python, SQL), advanced modeling (Tree-based, Neural Networks, Deep Learning), GenAI frameworks (LlamaIndex, LangGraph, etc.), and cloud platforms (AWS, GCP, Azure). Proven ability to architect scalable solutions, design comprehensive data strategies, and guide technical decision-making for complex AI/ML challenges and MLOps practices.

  • Domain Expertise & Industry Acumen: Extensive experience in financial services or fintech, with a strong emphasis on financial crime prevention and detection, including navigating compliance requirements, risk management, and regulatory frameworks.

  • Strategic Communication & Influence: The ability to influence senior leadership, translate complex technical concepts into strategic business language, build consensus across diverse stakeholder groups, and champion responsible AI practices.

  • Ownership & Pragmatism: Demonstrated ability to proactively identify impactful opportunities, influence business strategy, and drive initiatives to completion. You possess a pragmatic approach, effectively triaging requests and adapting analysis scope to achieve optimal outcomes in a fast-paced environment.

NICE TO HAVE BUT NOT ESSENTIAL

  • Education: Advanced degree (Masters / PhD) in Computer Science, Data Science, Machine Learning, Mathematics/Physics, or related quantitative fields preferred.

Additional Information

#LI-CH1

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.

Top Skills

AWS
Azure
GCP
Python
SQL

What the Team is Saying

Surendra
Smrithi
Pavan
Jennifer
Lindsay
Lauren
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The Company
8,000 Employees
Year Founded: 2011

What We Do

Wise is a global technology company, building the best way to move and manage the world's money. With Wise Account and Wise Business, people and businesses can hold 40 currencies, move money between countries and spend money abroad. Large companies and banks use Wise technology too; an entirely new network for the world's money. Launched in 2011, Wise is one of the world’s fastest growing, profitable tech companies. In fiscal year 2025, Wise supported around 15.6 million people and businesses, processing over $185 billion in cross-border transactions and saving customers around $2.6 billion.

Why Work With Us

We’re truly global in who we are, how we work, and how we build. Everything we do is centred around creating a world of money that’s fast, easy, fair. And open to all. Everyone who works here owns a piece of Wise, from the work they do, to the stock they hold.

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Wise Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

We expect new joiners in the office most days to build connections and learn from colleagues for their first six months. After that, most Wisers split their working week between the office and home, typically coming in at least 12 times a month.

Typical time on-site: Not Specified
Austin, TX
Brussels, BE
Hungary
Hyderabad, IN
Kuala Lumpur, MY
London, GB
New York, NY
São Paulo, BR
Singapore
Tallinn, EE
Tokyo, JP
Learn more

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