At a Glance
- Tasks: Use machine learning and AI to tackle scientific challenges and improve knowledge discovery.
- Company: Join LexisNexis Risk Solutions, a leader in innovative data solutions.
- Benefits: Enjoy flexible work hours, competitive salary, and a supportive work-life balance.
- Other info: Dynamic role with opportunities for growth in a fast-paced environment.
- Why this job: Make a real impact in science with cutting-edge technology and collaborative teams.
- Qualifications: Experience in data science, strong Python skills, and familiarity with LLMs required.
The predicted salary is between 60000 - 80000 £ per year.
LexisNexis Risk Solutions in Greater London seeks an experienced Data Scientist II. You will leverage machine learning, NLP, and generative AI to solve scientific challenges and enhance knowledge discovery. The role includes collaboration with cross-functional teams and involves extensive work with complex scientific data. Familiarity with LLMs and strong Python skills are essential. Additionally, we support a flexible work environment to promote work-life balance.
Data Scientist II: AI for Science & Knowledge Discovery in London employer: LexisNexis Risk Solutions
At LexisNexis Risk Solutions, we pride ourselves on being an excellent employer by fostering a collaborative and innovative work culture that empowers our Data Scientists to tackle complex scientific challenges. Our Greater London location offers a flexible work environment that promotes work-life balance, alongside ample opportunities for professional growth and development in cutting-edge technologies like machine learning and generative AI.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist II: AI for Science & Knowledge Discovery in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees at LexisNexis Risk Solutions on LinkedIn. A friendly chat can give us insider info and might even lead to a referral.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your machine learning projects, especially those involving NLP and generative AI. This will help us stand out during interviews.
✨Tip Number 3
Practice makes perfect! Get comfortable with common data science interview questions and coding challenges. We can even set up mock interviews with friends to boost our confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we can tailor our CV and cover letter to match the job description perfectly.
We think you need these skills to ace Data Scientist II: AI for Science & Knowledge Discovery in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with machine learning, NLP, and generative AI. We want to see how your skills align with the scientific challenges we tackle at LexisNexis.
Showcase Your Projects:Include specific examples of projects where you've used Python and worked with complex scientific data. This helps us understand your hands-on experience and problem-solving abilities.
Be Clear and Concise:When writing your cover letter, keep it straightforward. We appreciate clarity, so get straight to the point about why you’re a great fit for the Data Scientist II role.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensure you’re considered for the position.
How to prepare for a job interview at LexisNexis Risk Solutions
✨Know Your Tech
Make sure you brush up on your machine learning, NLP, and generative AI knowledge. Be ready to discuss specific projects where you've applied these technologies, as well as any challenges you faced and how you overcame them.
✨Showcase Your Python Skills
Since strong Python skills are essential for this role, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice common data manipulation tasks and algorithms beforehand.
✨Collaboration is Key
This role involves working with cross-functional teams, so be prepared to talk about your experience collaborating with others. Share examples of how you’ve successfully worked in a team setting, especially when dealing with complex scientific data.
✨Embrace Flexibility
With a focus on work-life balance, it’s important to express your understanding of flexible work environments. Discuss how you manage your time effectively and maintain productivity while working remotely or in a hybrid setup.
