Data Scientist Fraud Decisioning

Liberis; Greater London; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A global financial technology provider is looking for a Fraud Model Developer to enhance fraud strategies by leveraging deep data analysis. The position involves building and deploying models while monitoring their performance across various datasets. The ideal candidate will have 2–4 years of analytical fraud management experience, strong SQL proficiency, and the ability to communicate complex analytic results clearly. This role supports a hybrid working model requiring office presence at least 3 days a week.

Qualifications

• 2-4 years of experience in analytical fraud management with measurable impact.
• Up-to-date awareness of emerging fraud trends and controls.
• Hands-on modeling experience: feature engineering and validation.

Responsibilities

• Own global fraud decisioning and optimize for loss reduction.
• Build end-to-end models for fraud management.
• Monitor model performance and ensure data integration.

Skills

Analytical fraud management

SQL proficiency

Excel for analysis

Clear communication

Autonomous working style

Education

STEM background

Tools

Power BI

Looker

GCP exposure

Version control (Git)

Job description

Who are Liberis

At Liberis we are on a mission to unleash the power of small businesses all over the world - delivering the financial products they need to grow through a network of global partners.

At its core Liberis is a technology‑driven company bridging the gap between finance and small businesses. We use data and insights to help partners understand their customers’ real‑time needs and tech to offer tailor‑made financial products. Empowering small businesses to grow and keep their independent spirit alive is central to our vision.

Since 2007 Liberis has funded over 50,000 small businesses with over $3bn – but we believe there is much more to be done. Learn more about Liberis by visiting our team.

We are the Risk Analytics team with a goal to drive intelligent decision‑making by applying advanced statistical analytics to a wealth of the heart of the Risk function. Our focus is to deliver high‑quality fraud management for our customers around the world.

The Risk team is a global team with offices in London, Nottingham and Atlanta (US) covering Risk Analytics, Decision Analytics, Fraud Analytics, Underwriting and Collections. We’re on a mission to grow Liberis into the world’s leading embedded business finance provider and are looking for a Fraud Model Developer to help us make that happen!

The role

Are you energized by complex problems, real autonomy and the chance to innovate? If fraud management – and its constantly changing landscape – excites you, this is the role.

Reporting directly to the Director of Risk Analytics, you’ll use deep data analysis to design, build and productionise fraud strategies and models across the lifecycle, balancing loss reduction with healthy approval rates across large multi‑source datasets, run A/B and champion‑challenger tests, and turn analytics into clear deployable decision logic that moves the needle.

What you’ll be doing

• Own global fraud decisioning: rules, thresholds, step‑up controls optimised for EL reduction at stable approval rates.
• Build models end‑to‑end: problem framing, label/observation window design, sampling, feature engineering, training (logistic/GBM), calibration, back‑testing, validation, documentation and deployment into production decisioning.
• Experiment & ship: A/B and champion‑challenger tests; cost‑based optimisation; roll out winners quickly.
• Monitor & govern: Robust dashboards/alerts for model drift, PSI stability, leakage review, yield chargeback/refund ratios; publish a concise weekly fraud pack.
• Data & vendors: Evaluate new data sources and vendors, integrate where ROI is positive and track performance over time.
• Cross‑functional impact: Translate analytics into clear policies/playbooks; work with Product/Engineering to land decision logic cleanly and safely.

What we think you’ll need

• Experience in an analytical fraud management role with measurable impact (2–4 years, rough guide).
• Up‑to‑date awareness of emerging fraud trends and the latest controls to manage them with a habit of turning intel into tests, rules or model features quickly.
• Hands‑on modelling experience: feature engineering and building/validating fraud models; understanding of ROC/PR curves, Gini/KS, calibration, stability.
• SQL proficiency for data extraction; strong Excel for quick analysis.
• Ability to communicate clearly – turn complex analysis into crisp recommendations.
• Proactive autonomous working style; you know when to dive deep and when to align stakeholders.
• Experience deploying models to production or translating models into rules/strategies in a decision engine.
• Experience with Power BI or Looker for reliable self‑serve dashboards.
• GCP exposure and familiarity with version control (Git) are a plus.
• A solid STEM background helps – but aptitude and impact matter most.

What happens next

Think this sounds like the right next move for you? Or if you’re not completely confident that you fit our exact criteria, apply anyway and we can arrange a call to see if the role is fit for you. Humility is a wonderful thing and we are interested in hearing what you can add to Liberis!

Our hybrid approach

Working together in person helps us move faster, collaborate better and build a great Liberis culture. Our hybrid working policy requires team members to be in the office at least 3 days a week but ideally 4 days. At Liberis we embrace flexibility as a core part of our culture while also valuing the importance of the time our teams spend together in the office.

Key Skills

• Electrical
• Academics
• Customer Service
• Computer Data Entry
• Cardiac Surgery
• Freight Forwarding

Employment Type: Full Time

Experience: years

Vacancy: 1