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- Tasks: Lead innovative data science projects and support impactful business decisions.
- Company: Global biopharma leader focused on improving health worldwide.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Why this job: Make a real difference in global health through data-driven insights.
- Qualifications: Degree in a quantitative field and experience in healthcare data science.
- Other info: Collaborative team environment with a focus on innovation.
The predicted salary is between 48000 - 72000 £ per year.
A leading global biopharma company is seeking a Lead Data Scientist for their Enterprise AI Team in London. This role involves developing innovative data science products and working collaboratively to support business decisions.
Ideal candidates will have a degree in a quantitative field, with experience in data science applications, especially within healthcare. The successful applicant will communicate insights effectively and drive initiatives that align with the company's ambitious goals to improve global health.
Lead Data Scientist, Enterprise AI — Impactful Analytics employer: GlaxoSmithKline
Contact Detail:
GlaxoSmithKline Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist, Enterprise AI — Impactful Analytics
✨Tip Number 1
Network like a pro! Reach out to professionals in the biopharma and data science fields on LinkedIn. Join relevant groups and engage in discussions to get your name out there and learn about potential job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those related to healthcare. This will give you an edge and demonstrate your ability to develop innovative solutions.
✨Tip Number 3
Prepare for interviews by brushing up on your communication skills. Practice explaining complex data insights in simple terms, as this is crucial for driving business decisions in a collaborative environment.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Lead Data Scientist, Enterprise AI — Impactful Analytics
Some tips for your application 🫡
Showcase Your Skills: Make sure to highlight your experience in data science, especially in healthcare. We want to see how your skills can contribute to our innovative projects and support impactful business decisions.
Tailor Your Application: Don’t just send a generic CV! Customise your application to reflect the specific requirements of the Lead Data Scientist role. We love seeing how you align with our ambitious goals to improve global health.
Communicate Clearly: Since effective communication is key in this role, ensure your application clearly conveys your insights and experiences. We appreciate clarity and conciseness, so keep it straightforward!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity on our Enterprise AI Team.
How to prepare for a job interview at GlaxoSmithKline
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially those relevant to healthcare. Be ready to discuss your past projects and how you've applied data science techniques to solve real-world problems.
✨Showcase Your Communication Skills
Since the role involves communicating insights effectively, practice explaining complex data concepts in simple terms. Think of examples where you've successfully conveyed your findings to non-technical stakeholders.
✨Align with Their Goals
Research the company’s mission and recent initiatives in global health. Be prepared to discuss how your work can contribute to their ambitious goals and how you can drive impactful analytics within their team.
✨Collaborative Mindset
This role is all about teamwork, so be ready to share experiences where you've worked collaboratively. Highlight your ability to support business decisions through data-driven insights and how you can foster a positive team environment.
