At a Glance
- Tasks: Design and develop advanced analytics and machine learning solutions to solve real business challenges.
- Company: Join AbbVie, a leader in innovation and integrity within the healthcare industry.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative environment with strong career advancement potential.
- Why this job: Make a tangible impact by translating complex data into actionable insights.
- Qualifications: Bachelor's degree in a quantitative field; experience in data science and programming skills required.
The predicted salary is between 50000 - 70000 £ per year.
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.
Model Development and Deployment
- 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
- Bachelor's degree required in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, Physics, Machine Learning, or a related quantitative discipline experience.
- 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.
Data Scientist - New Position employer: AbbVie
AbbVie is an exceptional employer that fosters a collaborative and innovative work culture, particularly for the Data Scientist role. Located in a dynamic environment, employees benefit from comprehensive growth opportunities, competitive compensation, and a commitment to diversity and inclusion. With a focus on impactful projects in the healthcare sector, AbbVie empowers its team members to translate complex data into meaningful solutions that drive real-world change.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist - New Position
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who’s already in the data science field. Building relationships can open doors that job applications alone can't.
✨Show Off Your Skills
Create a portfolio showcasing your projects and models. Whether it's a GitHub repo or a personal website, having tangible examples of your work can really impress potential employers and give them a taste of what you can do.
✨Ace the Interview
Prepare for interviews by practising common data science questions and case studies. Don’t forget to brush up on your communication skills too—being able to explain complex concepts clearly is key to landing the job!
✨Apply Through Our Website
Don’t miss out on opportunities—apply directly through our website! It’s the best way to ensure your application gets seen by the right people and shows your genuine interest in joining our team.
We think you need these skills to ace Data Scientist - New Position
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the Data Scientist role. Highlight your experience with predictive models, machine learning, and any relevant projects that showcase your skills. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how your background aligns with our needs. Don’t forget to mention specific examples of your work that relate to the job description.
Showcase Your Technical Skills:We’re looking for strong programming skills in Python, R, or similar languages. Make sure to include any relevant technical projects or experiences that demonstrate your expertise in statistical modelling and machine learning.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensure it gets the attention it deserves. We can’t wait to see what you bring to the table!
How to prepare for a job interview at AbbVie
✨Know Your Models Inside Out
Make sure you can explain the models you've developed in detail. Be ready to discuss the algorithms you used, why you chose them, and how they solved specific business problems. This shows your technical expertise and ability to translate complex concepts into practical solutions.
✨Prepare for Stakeholder Questions
Since this role involves partnering with various stakeholders, anticipate questions about how you would approach their specific business challenges. Think of examples where you've successfully collaborated with non-technical teams and how you communicated your findings effectively.
✨Showcase Your Programming Skills
Be prepared to demonstrate your programming skills, particularly in Python or R. You might be asked to solve a problem on the spot, so brush up on your coding abilities and be ready to explain your thought process as you work through it.
✨Visualisation is Key
Practice how you present your data insights. Use visualisation techniques to tell a story with your data. Being able to convey complex analyses in a clear and engaging way will set you apart, especially when addressing both technical and non-technical audiences.
