Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more. Experian invests in people and new advanced technologies to unlock the power of data. We have an amazing team of 25,200 people in 32 countries.

As a Senior Data Scientist you will lead research, development and client-focused innovation across our fraud analytics portfolio by creating solutions that strengthen fraud detection, digital trust and risk decisioning across markets. You will evaluate and integrate data assets while balancing multiple concurrent projects, anticipating risks and deliver outcomes. You will invent machine learning, graph, behavioural and GenAI methods to structured and unstructured data; and convert prototypes into reusable capabilities on the Ascend platform.

The product scope includes fraud analytics and decisioning solutions, unified digital intelligence, device fingerprinting and behavioural intelligence, trade-delete and credit-washing analytics, GenAI fraud assistants.

You will report to Director of Data Science and GenAI.

What you'll do:

• Analyze large-scale fraud, credit, device, behavioral and digital-interaction data to identify risk and trust signals.
• Develop fraud models, scores, attributes, device profiles and graph-based capabilities for AFS and related solutions.
• Apply advanced machine learning, graph analytics, deep learning and GenAI methods to complex fraud challenges.
• Evaluate and measure value of new data assets.
• Build scalable data pipelines, reusable analytical tools, automation templates and production-ready solutions on Ascend.

   

What you'll bring:

• 5–7+ years of relevant experience in data science, AI, predictive modeling or advanced analytics, including ownership of complex, hands-on innovation and client-focused projects.
• 7+ years of experience developing data and automation pipelines and transitioning analytical prototypes into monitored, scalable production solutions; Knowledge in modern ML and deep-learning tooling and LLM and agent-based development frameworks.
• Understanding of when and how to apply regression, machine learning, AI, deep learning, clustering, gradient boosting, graph algorithms, anomaly and pattern detection, and Gen AI.
• Command of model validation, including cross-validation, regularization, Bayesian methods, in-sample versus out-of-sample testing, statistical significance tests and Monte Carlo simulation.
• Write near-production-level Python code; experience with PySpark and distributed data processing.

   

   

   

What you will get:

• Personal Development - career pathway for professional growth supported by learning and development programs and unlimited access to online educational training courses, learning materials and books.
• Work environment - excellent work conditions with friendly environment, recognized team spirit, and fun and quality recreation time.
• Social benefit package including life insurance, food vouchers, additional health insurance, monthly flex allowance and internet coverage, corporate discounts, marriage and childbirth / adoption allowance, Multisport card, Sharesave plan, Employee assistance program, а birthday gift and many other benefits!
• Work-life balance - 25 days paid vacation, 1 additional day off for your birthday and extra 3 paid days for participation in Social responsibility event.
• Opportunity for Flexible working hours and Home Office.

Experian is an Equal opportunity employer. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

#LI-Hybrid

This is a hybrid remote/in-office role.

Recruitment Fraud Awareness - Experian's recruitment process is conducted only through authorised channels. Recruitment communications will only be sent from an @experian.com email address. Experian will never ask candidates to make any payment as part of an application, interview, assessment, onboarding, or recruitment process. To apply for roles or verify opportunities, please visit experian.com/careers.

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