Data Scientist (Contract)

Company Description

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.

Our uniqueness is that we celebrate yours. Experian's people first, inclusive and purpose driven culture is multi award-winning; World's Best Workplaces™ 2025 (Fortune Global Top 25), Great Place To Work™ in 26 countries to name a few. Check out Experian Life on social or explore our Careers Site to understand why. Experian is also proud to be an Equal Opportunity and Affirmative Action employer. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

Job Description

We'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.

Qualifications

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

   

Additional Information

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

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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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