Data Scientist
HybridMaidenhead, England, United Kingdom
Job Summary
Design, develop, and maintain predictive and prescriptive models to translate commercial problems into analytical solutions that drive measurable business value. Partner with stakeholders to define use cases, requirements, and success criteria, then work cross-functionally with business analysts and technical teams to deploy scalable, compliant analytics from concept to production. Maintain, optimize, and refresh existing models while ensuring projects are delivered on time, within budget, and aligned with governance standards. Communicate model logic and business implications clearly to both technical and non-technical audiences, using visualization to support decision-making. This role supports global and affiliate-led AI initiatives within AbbVie's immunology, oncology, and neuroscience therapeutic areas.
Required Qualifications
- Bachelor's degree required in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, Physics, Machine Learning, or a related quantitative discipline
- Relevant experience in data science, machine learning, AI, advanced analytics, or statistical modelling
- Demonstrated experience developing and applying predictive, prescriptive, or machine learning solutions that have delivered business impact
- Strong expertise in statistical modelling, machine learning, predictive analytics, and advanced analytical techniques
- Strong programming skills in Python, R, or similar analytical languages
- Experience in model development, validation, deployment, maintenance, and performance monitoring in a business environment
- Ability to work with complex, incomplete, or imperfect datasets and develop practical solutions around data limitations
- Strong stakeholder management skills and experience translating unstructured business problems into analytical solutions and actionable recommendations
- Excellent communication and presentation skills, with the ability to explain complex analytical concepts to both technical and non-technical audiences
- Understanding of coding best practices, reproducibility, model governance, and documentation standards
- Experience working cross-functionally with business, analytics, and technical teams in a matrix environment
Desired Qualifications
- Master's degree or higher in a relevant quantitative field
- Pharmaceutical, healthcare, NHS, or other regulated industry experience
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