Lead Data Scientist - Fraud

Who We Are

Provenir is a global fintech company with offices across North America, the UK, and Singapore backed by talented teams across APAC, EMEA, and LATAM. Provenir helps fintechs, financial institutions, and payment providers make smarter decisions, faster. We are passionate about technology and empowering businesses to become industry leaders. As a leading provider of decisioning and analytics products for financial services and other industries, we empower businesses to create digital-first decisioning solutions that drive business growth. If you’d like to work at an innovative fintech with a global footprint that is redefining the industry, then we want you!

📍 Remote first - UK

🛠️ Fraud SME, ML/AI, Graph Analytics

🚀 Build and lead the data science function for our profiling platform

🕛 10+ years in data science with deep fraud expertise

💰 Competitive compensation

💚 Fantastic benefits including Health Plans, WFH allowance and Macbook Pro

We are Provenir AI, part of the Provenir group, a global fintech company with a passion for technology and helping businesses become industry leaders. As a leading provider of decisioning and analytics products for financial services and other industries, we empower businesses to create innovative, digital-first financial decisioning solutions that drive business growth.

We need someone who genuinely understands fraud. You'll lead a new data science function primarily focussed on our customer profiling engine. Your engineering team are strong technically but need a fraud expert who can guide what to build, how detection should evolve, and what signals matter. You'll be the go-to person on all things fraud whilst building out the data science capabilities around it.

This isn't a role where you can learn fraud on the job. We need someone with proven fraud expertise - you'll have built detection models in production, understood how fraud patterns evolve, managed the challenges of false positives, and delivered systems that demonstrably prevent fraud.

Your Responsibilities 🚀

• Collaborate with Product team on the fraud detection and data science strategy for our profiling engine

• Develop and enhance ML models that catch application fraud across lending, payments and other financial products

• Design detection approaches that adapt as fraud patterns evolve

• Create scoring models that balance fraud prevention with customer experience

• Work with engineering to translate fraud expertise into production systems

• Establish monitoring and measurement frameworks for fraud model performance

• Build and mentor a data science team as we grow

Your Experience 🛠️

• 10+ years in data science with at least 5 years focused on fraud detection

• Deep expertise in fraud - synthetic identities, first-party fraud, fraud rings, mule accounts

• Proven track record building and deploying fraud models in production environments

• Strong understanding of fraud typologies and how they evolve across different financial products

• Experience with imbalanced datasets, fraud labelling challenges and model performance in adversarial environments

• Hands-on experience with Python and ML frameworks

• Understanding of MLOps practices - deployment, monitoring, challenger models, performance decay

• Experience working with real-world fraud data and messy identity information

• Comfortable working autonomously and being the fraud expert in the room

We'd also love to see:

• Experience with real-time/low-latency fraud scoring

• Understanding of fraud investigation workflows and how models support fraud ops teams

• Network analysis or graph techniques for detecting fraud rings and collusion

• Experience with explainable AI for fraud decisioning

• Knowledge of regulatory requirements around fraud prevention (AML, KYC, sanctions screening)

• Experience building or leading data science teams

• Work history at fraud prevention vendors, fintechs or financial services fraud teams

What you should know about this role

This is about fraud expertise first, data science second. If you're a brilliant generalist data scientist who's keen to move into fraud, this isn't the right role. We need someone who already knows the domain.

You'll be autonomous from day one. There's no fraud analytics function to join - you're building it. The engineering team will look to you as the fraud expert to guide technical decisions. If you need a lot of structure or mentorship, this won't suit you.

You'll have genuine influence over your data science tooling and environment. We know data scientists are often frustrated by inadequate tools or rigid infrastructure that gets in the way of doing good work. You'll have support to shape how we build the data science environments going forward.

You'll be hands-on initially - writing code, building models, deploying systems. Team building comes later once foundations are established.

You'll work closely with engineers who understand how to build systems but need your fraud expertise to know what to build. Credibility comes from shipping capabilities that prevent fraud and working collaboratively with the engineering team.

Interview Process 💬

• Initial chat. With our recruitment team to understand your background, particularly your fraud experience, and what you're looking for

• Technical Interview. With the CTO and engineering leadership, focused on your fraud expertise, how you've approached fraud problems in production, and team building

• Case Study. We'll present a realistic scenario and discuss your approach to solving it

• Final Interview. Cultural fit, working style, and how you'd approach the first 90 days

Your Benefits 💚

• Comprehensive private health cover and wellness plans

• Flexible and remote-friendly opportunities

• Maternity/paternity leave

• Retirement benefits such as pension contributions to plan for your future

• Macbook Pro

Our employees are our top priority; we offer comprehensive health and wellness plans. You will enjoy paid time off and company holidays, flexible and remote-friendly opportunities, and maternity/paternity leave.

At Provenir, we recognize that diversity and inclusion make our teams stronger. We are committed to equal employment opportunity and welcome everyone regardless of race, colour, ancestry, religion, national origin, age, sex, gender identity, sexual orientation, disability, marital status, domestic partner status, citizenship, or veteran status or medical condition. We encourage people from all backgrounds to apply.