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- Tasks: Lead a team to develop cutting-edge fraud detection systems using AI and machine learning.
- Company: Join Wise, a global tech company revolutionising money management.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Why this job: Make a real impact in safeguarding customers while innovating in the fintech space.
- Qualifications: 3+ years of leadership in data science with expertise in AI/ML technologies.
- Other info: Diverse and inclusive environment that values unique perspectives and experiences.
The predicted salary is between 48000 - 84000 ÂŁ per year.
Wise is a global technology company, building the best way to move and manage the world’s money. 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.
The Fraud team at Wise is dedicated to safeguarding our platform against financial crime and ensuring the protection of our legitimate customers. Leveraging cutting‑edge machine learning, real‑time transaction monitoring, and data analysis, our team is responsible for developing and enhancing fraud detection systems. Software engineers, data analysts, and data scientists collaborate on a daily basis to continuously improve our systems and provide support to our fraud investigation team.
Our Vision Is
- Build a globally scalable fraud 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 fraud investigators and the product team to develop solutions that leverage the expertise of fraud prevention specialists.
- Not only meet the requirements set by regulators and auditors but also surpass their expectations.
How You’ll Be Contributing
- Strategic Technical Leadership: Drive the technical vision for next‑generation model architectures including transformers, agentic AI, and computer vision applications. Make key decisions on technology adoption and guide your team through complex technical challenges.
- Team Development & Mentorship: Lead and grow our technical team, mentoring data scientists on cutting‑edge technologies and methodologies. Build technical capabilities across the team while fostering career development and knowledge sharing.
- Cross‑Functional Leadership: Partner strategically with Product, Engineering, and Operations leaders to ensure that data science is effectively used to enhance product roadmaps. Influence stakeholders to ensure technical solutions deliver maximum customer and business value.
- Delivery Excellence: Establish and oversee scalable deployment strategies and MLOps practices. Lead your team in implementing robust model monitoring, A/B testing frameworks, and performance tracking to ensure production success.
- Technical Strategy: Design comprehensive data strategies and oversee large‑scale model optimization efforts. Ensure your team delivers high‑quality model outputs that meet business requirements.
- Organizational Impact: Define and enforce technical standards, model governance frameworks, and best practices across all data science projects. Drive process improvements that accelerate iteration speed and delivery quality.
- Innovation Culture: Shape the research agenda and evaluate emerging AI/ML technologies for strategic adoption. Foster a culture of experimentation and continuous learning while making informed decisions about resource allocation.
- Responsible AI Leadership: Champion ethical AI practices across the organization, establishing frameworks for bias mitigation and transparency while guiding the team in responsible AI development.
- Customer impact: Strengthen a culture that prioritises tangible customer solutions and measurable impact over isolated experiments.
A Bit About You
- Leadership Experience: 3+ years of leading data science teams and driving the development of production‑grade ML and AI systems that operate at scale and directly impact user experience. Proven track record of building and scaling technical teams while delivering measurable business outcomes.
- Industry Expertise: Experience in financial services, fintech, or other regulated industries is highly valued, with leadership experience navigating compliance requirements, risk management, and regulatory frameworks.
- Technical Leadership Depth: Strong technical foundation with expertise in Python, neural networks, and ML and GenAI frameworks (TensorFlow, PyTorch, LlamaIndex, LangGraph) that enables credible technical decision‑making and effective team guidance on complex AI/ML challenges.
- Strategic Technology Vision: Experience with cloud platforms (AWS, GCP, Azure) and modern MLOps practices, with ability to architect scalable solutions and guide technical strategy for model deployment and infrastructure decisions.
- Team Development: Exceptional ability to mentor, develop, and retain top technical talent while fostering collaborative and innovative team cultures. Track record of growing team capabilities and establishing technical excellence standards.
- Executive Communication: Outstanding ability to influence and communicate with senior leadership, translating complex technical concepts into strategic business language and building consensus across diverse stakeholder groups.
- Organizational Impact: Champion of responsible AI practices with experience establishing ethical frameworks and driving cultural change around fairness, transparency, and societal impact across technical organizations.
We’re people without borders — without judgement or prejudice, too. We want to work with the best people, no matter their background. So if you’re passionate about learning new things and keen to join our mission, you’ll fit right in. Also, qualifications aren’t that important to us. If you’ve got great experience, and you’re great at articulating your thinking, we’d like to hear from you. And because we believe that diverse teams build better products, we’d especially love to hear from you if you’re from an under‑represented demographic. 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.
Senior Data Science Manager - Fraud Risk employer: Wise
Contact Detail:
Wise Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Science Manager - Fraud Risk
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Wise. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Prepare for interviews by diving deep into Wise's mission and values. Show us how your experience aligns with our goals in fraud prevention and data science. We love candidates who are genuinely passionate about what we do!
✨Tip Number 3
Don’t just talk about your skills; demonstrate them! If you have a portfolio or projects showcasing your data science prowess, bring them along. We want to see your work in action!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows us you're serious about joining the Wise team. Let’s make money management easier together!
We think you need these skills to ace Senior Data Science Manager - Fraud Risk
Some tips for your application 🫡
Show Your Passion: When writing your application, let your enthusiasm for data science and fraud prevention shine through. We want to see how your passion aligns with our mission at Wise to make money management easier and safer for everyone.
Tailor Your Experience: Make sure to highlight your relevant experience in leading data science teams and working with machine learning technologies. We’re looking for specific examples that demonstrate your ability to drive impactful results in a fast-paced environment.
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to explain your technical skills and leadership experience. We appreciate well-structured applications that make it easy for us to see your qualifications.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensure you’re considered for the role. Plus, it shows you’re serious about joining our team at Wise.
How to prepare for a job interview at Wise
✨Know Your Tech Inside Out
Make sure you’re well-versed in the latest machine learning techniques and frameworks like TensorFlow and PyTorch. Be ready to discuss how you've applied these technologies in real-world scenarios, especially in fraud detection or risk management.
✨Showcase Your Leadership Skills
Prepare examples of how you've led data science teams and mentored others. Highlight your experience in building technical capabilities and fostering a collaborative culture, as this role requires strong team development skills.
✨Understand the Business Impact
Be prepared to discuss how your technical decisions have driven measurable business outcomes. Think about specific instances where your work has directly improved user experience or contributed to compliance in a regulated industry.
✨Communicate Like a Pro
Practice translating complex technical concepts into simple terms. You’ll need to influence senior leadership and collaborate with cross-functional teams, so being able to articulate your ideas clearly is crucial.
