AbbVie Logo

AbbVie

Data Scientist

Posted 21 Days Ago
Be an Early Applicant
Hybrid
Maidenhead, Berkshire, England, GBR
Entry level
Hybrid
Maidenhead, Berkshire, England, GBR
Entry level
Designs, deploys, and maintains predictive and prescriptive models and advanced analytics solutions for business needs. Partners with stakeholders to translate commercial problems into analytical frameworks, move solutions into production, and ensure compliance, governance, and measurable business impact. Communicates model outputs and recommendations to technical and non-technical audiences while collaborating cross-functionally across business, analytics, and technical teams.
The summary above was generated by AI
Company Description

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.co.uk. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.

Job Description

  • Located in Maidenhead
  • Reporting to Head of Business Intelligence 

Job Overview

The Data Scientist is responsible for designing, developing, scaling, and maintaining advanced analytics and machine learning solutions for the affiliate. The role translates business questions into robust analytical frameworks and predictive or prescriptive models that improve decision-making and deliver measurable business value.

Working across business and technical teams, the Data Scientist partners with stakeholders to define use cases, requirements, timelines, and success criteria, and supports the deployment of scalable, compliant, and sustainable analytics solutions. The role combines strong technical capability in data science, statistics, and programming with business acumen, communication skills, and a practical delivery focus.

Key responsibilities

Advanced analytics and modelling

  • Design, develop, deploy, and maintain predictive and prescriptive models to address affiliate business needs.
  • Translate commercial problems into mathematical, statistical, and analytical approaches.
  • Apply machine learning and advanced analytics methods to solve complex business challenges.
  • Build reliable, scalable, and modular solutions using datasets of varying quality and completeness.
  • Maintain, optimise, and refresh existing models to ensure continued performance and value.

Business partnering and delivery

  • Partner with stakeholders to define business questions, requirements, timelines, objectives, and success criteria for data science initiatives.
  • Work closely with Business Analysts, Data Analysts, BTS, and technical partners to move solutions from concept or pilot into production.
  • Ensure projects are delivered on time, accurately, within budget, and in line with compliance and governance requirements.
  • Support validation, user acceptance, and effective handover of solutions to business users and partner teams.
  • Contribute to the deployment of global and affiliate-led analytics, automation, and AI initiatives.

Communication and impact

  • Communicate model logic, assumptions, outputs, and business implications clearly to technical and non-technical audiences.
  • Translate complex analyses into clear, practical recommendations for decision-makers.
  • Use effective visualisation and storytelling approaches to support understanding and action.
  • Build strong working relationships across business and technical teams, establishing credibility through technical rigour and business relevance.

Qualifications

Qualifications & Competencies

  • Bachelor’s degree required in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, Physics, Machine Learning, or a related quantitative discipline experinece.
  • Master’s degree or higher in a relevant quantitative field preferred.
  • 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.
  • Pharmaceutical, healthcare, NHS, or other regulated industry experience preferred.

Additional Information

AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community.  Equal Opportunity Employer/Veterans/Disabled. 

US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html

US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:

https://www.abbvie.com/join-us/reasonable-accommodations.html

AbbVie London, England Office

London, United Kingdom

Similar Jobs

2 Days Ago
Hybrid
Entry level
Entry level
Digital Media • Gaming • Software • Esports • Automation
Develop machine learning models, perform statistical analysis, and extract actionable insights from large datasets. Responsibilities include data sourcing and validation, exploratory analysis, predictive modeling, A/B testing, scalable data science infrastructure, stakeholder collaboration, and communicating findings through visualizations and presentations. The role supports data-driven decisions across fraud, responsible gambling, trading, branding, sports, and gaming products.
Top Skills: Artificial IntelligenceBig Data TechnologiesCloud ComputingData VisualizationData WarehousingDeep LearningDistributed SystemsMachine LearningPythonRSQL
2 Days Ago
Hybrid
Entry level
Entry level
Digital Media • Gaming • Software • Esports • Automation
Develop machine learning and statistical models, analyze large datasets, conduct exploratory analysis and controlled experiments, and deliver actionable insights for sports and gaming products. The role partners with Fraud, Responsible Gambling, Trading, Branding, and other stakeholders to solve business problems, maintain scalable data science infrastructure, communicate findings, and promote innovative data science practices.
Top Skills: A/B TestingArtificial IntelligenceBig Data TechnologiesCloud ComputingData Science Libraries And FrameworksData VisualizationData WarehousingDeep LearningDistributed SystemsMachine LearningPythonRSQL
12 Days Ago
Hybrid
London, Greater London, England, GBR
Expert/Leader
Expert/Leader
Financial Services
Leads end-to-end development and production deployment of machine learning, generative AI, and agentic solutions for payments and banking. Responsibilities include problem framing, experimentation, evaluation, MLOps, LLMOps, governance, monitoring, scalable cloud architecture, security, and systems integration. The role establishes reusable AI capabilities, partners with cross-functional stakeholders, mentors technical teams, and communicates model outcomes and operational tradeoffs to technical and non-technical audiences.
Top Skills: Agentic SystemsAmazon BedrockAmazon SagemakerAPIsAWSBatch ProcessingCloud InfrastructureContainerizationContinuous Integration And DeliveryDistributed SystemsEvent-Driven ArchitectureFeature StoresGenerative AiLarge Language ModelsLlmopsMachine LearningMcpMlopsModel RegistriesMulti-Agent OrchestrationNlpNumpyPandasPrompt RegistriesPythonPyTorchRetrieval-Augmented GenerationScikit-LearnScipyStatsmodelsStreamingTensorFlowTool And Function Calling

What you need to know about the London Tech Scene

London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account