At a Glance
- Tasks: Design and deploy data models, analyse complex datasets, and collaborate globally.
- Company: Global organisation at the forefront of data science and AI-driven decision-making.
- Benefits: Competitive salary up to £50,000, bonus, and hybrid working in Central Newcastle.
- Other info: Opportunity to work with Generative AI tools and advance your career.
- Why this job: Shape the future of finance with cutting-edge analytics and AI technologies.
- Qualifications: Proven experience in Data Science, with skills in data querying and analysis.
The predicted salary is between 45000 - 50000 € per year.
We’re hiring a Data Scientist for a global organisation operating at the intersection of data, analytics, and AI‑driven decision‑making. This is a highly influential role, sitting at the forefront of data science strategy and shaping how advanced analytics and AI are applied across complex, real‑world problems in finance.
Responsibilities
- Design, development, and deployment of models and algorithms into production
- Analyse large, complex datasets to identify patterns and trends, translating insights into actionable product recommendations
- Collaborate with global teams across product, engineering, and analytics to deliver high‑quality, scalable solutions
- Establish and uphold best practices across data science methodologies, including data preparation, model validation, and performance monitoring
- Stay close to industry trends and emerging technologies, particularly in AI and GenAI
What we’re looking for
- Strong, proven experience across Data Science, with exposure to Data Engineering and/or Machine Learning
- Ability to operate autonomously within a global, distributed organisation
- Solid experience selecting and applying appropriate methodologies, technologies, and techniques
- Hands‑on experience with data querying, manipulation, and analysis, including tools such as Pandas and NumPy
Nice to have
- Experience working with Generative AI tools and approaches
- Software engineering or programming experience, ideally in Python
- Advanced academic background in Computer Science, Data Science, or equivalent industry experience
Hybrid Working in Central Newcastle Up to £50,000 + bonus
Data Scientist - Newcastle - Asset Management in Newcastle upon Tyne employer: Energy Jobline ZR
Join a forward-thinking global organisation in Newcastle upon Tyne, where as a Data Scientist, you will be at the cutting edge of data science strategy within the asset management sector. Enjoy a collaborative work culture that values innovation and offers extensive opportunities for professional growth, alongside competitive benefits including a hybrid working model and performance bonuses. This role not only allows you to influence real-world financial decisions but also positions you within a vibrant city known for its rich history and dynamic tech scene.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist - Newcastle - Asset Management in Newcastle upon Tyne
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data analysis and AI. This is your chance to demonstrate what you can do beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in data science. Be ready to discuss how you've applied methodologies and tools like Pandas and NumPy in real-world scenarios.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented data scientists like you. Plus, it’s a great way to ensure your application gets noticed!
We think you need these skills to ace Data Scientist - Newcastle - Asset Management in Newcastle upon Tyne
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role. Highlight your experience with data science methodologies, tools like Pandas and NumPy, and any relevant projects that showcase your skills in AI and analytics.
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 mission at StudySmarter. Don’t forget to mention any experience with Generative AI if you have it!
Showcase Your Projects:If you've worked on any interesting data science projects, make sure to include them in your application. We love seeing real-world applications of your skills, so share what you've done and the impact it had!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status directly!
How to prepare for a job interview at Energy Jobline ZR
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals. Be ready to discuss your experience with data querying, manipulation, and analysis using tools like Pandas and NumPy. Prepare to showcase how you've applied these skills in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Since this role involves tackling complex, real-world problems, think of specific examples where you've designed and deployed models or algorithms. Be prepared to explain your thought process and the impact of your solutions on previous projects.
✨Collaboration is Key
This position requires working with global teams, so highlight your experience in collaborative environments. Share examples of how you've worked with product, engineering, and analytics teams to deliver scalable solutions and maintain best practices.
✨Stay Ahead of the Trends
Familiarise yourself with the latest trends in AI and Generative AI. Be ready to discuss how these technologies can be applied in asset management and how you've kept your skills current. Showing that you're proactive about learning will impress the interviewers.
