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.
Job DescriptionAs 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.
- Validate model performance, stability, fairness, explainability and growth.
- Lead analytical and productization workstreams.
- Apply advanced algorithms to business problems and move solutions from research or prototype into production or client use.
- Translate technical findings into recommendations.
- Partner across multiple geographically distributed teams.
- Mentor colleagues, share expertise and promote responsible AI and reproducible practices.
- Maintain knowledge of fraud trends, digital intelligence, regulation, GenAI and latest analytical technologies.
- Measure benefits and explain trade-offs.
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.
- Grasp of probability, statistical inference, optimization, linear algebra and calculus
- 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.
- Knowledge in modern ML and deep-learning tooling and LLM and agent-based development frameworks.
- Understanding of large-scale data technologies, cloud platforms, NoSQL and graph databases, time-series data and tools for unstructured information.
- Knowledge of fraud risk, identity, device fingerprinting, digital or behavioral intelligence, credit-washing analytics, credit risk, fraud graphs or fraud strategy optimization.
- Understanding of model governance, responsible AI, explainability, privacy, security and regulatory considerations relevant to fraud and digital-interaction data.
- Interest and experience mentoring colleagues and providing technical leadership.
- Advanced technical/quantitative degree or equivalent experience.
- Fluent English
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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Skills Required
- 5-7+ years of relevant experience in data science, AI, predictive modeling, or advanced analytics
- 7+ years developing data and automation pipelines and transitioning analytical prototypes into scalable production solutions
- Knowledge of probability, statistical inference, optimization, linear algebra, and calculus
- Experience applying regression, machine learning, AI, deep learning, clustering, gradient boosting, graph algorithms, anomaly detection, pattern detection, and generative AI
- Expertise in model validation, including cross-validation, regularization, Bayesian methods, statistical significance testing, and Monte Carlo simulation
- Near-production-level Python programming and PySpark or distributed data processing experience
- Knowledge of modern machine learning, deep learning, large language model, and agent-based development frameworks
- Understanding of large-scale data technologies, cloud platforms, NoSQL databases, graph databases, time-series data, and unstructured information tools
- Knowledge of fraud risk, identity, device fingerprinting, digital or behavioral intelligence, credit-washing analytics, credit risk, fraud graphs, or fraud strategy optimization
- Understanding of model governance, responsible AI, explainability, privacy, security, and regulatory considerations
- Experience mentoring colleagues and providing technical leadership
- Advanced technical or quantitative degree, or equivalent experience
- Fluent English
Experian Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Experian and has not been reviewed or approved by Experian.
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Healthcare Strength — Medical and dental coverage is described as strong, with expanded mental health resources and telemedicine options. Coverage includes inclusive services such as gender transition and fertility support.
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Leave & Time Off Breadth — Time-off offerings are generous, including substantial PTO/vacation, paid holidays, and paid volunteer days with options to purchase additional leave. Parental leave is available for birth and non-birth parents alongside flexible working arrangements that support work-life balance.
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Retirement Support — Retirement programs include a 401(k) with company matching and contributory pension schemes in some regions. These elements complement base pay and bonuses to form a competitive total rewards package.
Experian Insights
What We Do
Experian unlocks the power of data to create opportunities for consumers, businesses and society. During life’s big moments – from buying a home or car, to sending a child to college, to growing a business exponentially by connecting it with new customers – we empower consumers and our clients to manage data with confidence so they can maximize every opportunity. We gather, analyse and process data in ways others can’t. We help individuals take financial control and access financial services, businesses make smarter decision and thrive, lenders lend more responsibly, and organizations prevent identity fraud and crime. For more than 125 years, we’ve helped consumers and clients prosper, and economies and communities flourish – and we’re not done. Our 20,600 people in 43 countries believe the possibilities for you, and our world, are growing. We’re investing in new technologies, talented people and innovation so we can help create a better tomorrow. About Experian: Bringing data to life requires creativity, passion, flexibility and expertise. We want you to share in our success. That's why we offer rewards that recognise great performance. Working in a culture of collaboration, achievement and respect we will give you the support and encouragement you need to develop your skills and talents and progress your career. Everyday our people bring enthusiasm, innovation and inspiration to work and if this sounds like you connect with us at Experian.
