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.
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Job DescriptionWe're looking for an intermediate Data Scientist to join our Data Science team on a 12-month contract.
The team works across established and emerging data products and analytical initiatives within Experian Marketing Services. Current priorities include the Mosaic refresh, Audience Taxonomy and Spend Analytics, alongside new machine-learning and AI opportunities across our consumer and commercial businesses.
This is a hands-on role where you'll apply statistical analysis, experimentation and machine learning to real business and product problems. Working within a multidisciplinary scrum team, you'll take analytical work from problem definition and data exploration through modelling and validation, collaborating with Product, Data Engineering and other stakeholders to turn data science into practical outcomes. You will report to Data Science and Engineering Manager
What you'll be doing:
Analyse complex datasets to identify patterns and insights that inform product and business decisions.
Develop and evaluate statistical and machine-learning models, including data preparation, feature engineering, model selection, validation and performance monitoring.
Design and analyse experiments using methods such as regression analysis, hypothesis testing and A/B testing.
Contribute to data science and AI initiatives, including Mosaic, Audience Taxonomy, Spend Analytics, embeddings, retrieval-augmented generation (RAG) and prompt engineering, where relevant.
Collaborate with scrum teams and stakeholders to translate requirements into reliable analytical solutions, document methodologies and communicate findings clearly to technical and non-technical audiences.
What we're Looking:
5 years of working experience applying data science and machine-learning techniques to business or product challenges, ideally within marketing analytics, customer segmentation, audience analytics or a related customer-data environment.
Proficiency in Python and SQL for analysing large and complex datasets, using libraries such as pandas, scikit-learn or similar tools.
Strong knowledge of statistics, experimentation and machine learning, including regression, hypothesis testing, experimental design, feature engineering, model selection and evaluation.
Experience working with modern cloud data platforms, such as Snowflake, and the ability to structure and solve complex or ambiguous problems.
Clear communication, planning and collaboration skills, with the ability to work independently and partner effectively with Data Science, Engineering, Product and business teams across locations, time zones and changing priorities.
Additional Experience That Would Be Valuable:
Experience with generative AI and large language model applications, including embeddings, retrieval-augmented generation (RAG), vector search or prompt engineering.
Knowledge of deep-learning techniques or experience working with large-scale datasets.
Experience developing analytical solutions into repeatable products, capabilities or business processes.
Exposure to model validation, monitoring and ongoing performance evaluation.or
Benefits/Perks:
- Great compensation package and discretionary bonus plan
- Hybrid work arrangement - 2 days WFO and 2 days WFH
- Experian is an equal opportunities employer
#LI-Hybrid
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Skills Required
- Five years of experience applying data science and machine-learning techniques to business or product challenges
- Experience in marketing analytics, customer segmentation, audience analytics, or a related customer-data environment
- Proficiency in Python and SQL for analyzing large and complex datasets
- Experience using libraries such as pandas and scikit-learn or similar tools
- Strong knowledge of statistics, experimentation, and machine learning
- Experience with regression, hypothesis testing, experimental design, feature engineering, model selection, and evaluation
- Experience with modern cloud data platforms such as Snowflake
- Ability to structure and solve complex or ambiguous problems
- Clear communication, planning, and collaboration skills
- Ability to work independently and partner with Data Science, Engineering, Product, and business teams
- Experience with generative AI and large language model applications, including embeddings, retrieval-augmented generation, vector search, or prompt engineering
- Knowledge of deep-learning techniques or experience working with large-scale datasets
- Experience developing analytical solutions into repeatable products, capabilities, or business processes
- Exposure to model validation, monitoring, and ongoing performance evaluation
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.
