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- Tasks: Support analytics delivery and apply machine learning to uncover insights.
- Company: Join a dynamic team at the forefront of strategy and innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make a real impact by solving real-world problems with data.
- Qualifications: Experience in data science and proficiency in Python or R.
- Other info: Collaborative environment with a focus on innovation and creativity.
The predicted salary is between 30000 - 50000 £ per year.
We’re hiring a Data Scientist to join a growing team working at the intersection of strategy, analytics, and innovation. This is a great opportunity for someone who’s curious, technically sharp, and enjoys solving real-world problems with data. You’ll play a key role in delivering high-impact analytics projects across a variety of industries helping shape decision-making through smart insights and modelling.
What you’ll be doing:
- Supporting end-to-end analytics delivery across diverse client projects
- Applying statistical methods and machine learning to uncover insights
- Communicating findings in a simple, impactful way to stakeholders
- Collaborating closely with cross-functional teams
- Contributing to internal innovation, tools, and ways of working
What you’ll bring:
- Solid experience in data science, analytics, or a related field
- Proficiency in Python, R or other modern data tools
- Strong grasp of machine learning and statistical techniques
- Ability to explain complex ideas clearly to different audiences
- A problem-solving mindset and attention to detail
Data Scientist in London employer: ENI – Elizabeth Norman International
Contact Detail:
ENI – Elizabeth Norman International Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in London
✨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 machine learning and analytics. This will give potential employers a taste of what you can do and how you solve real-world problems.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and practising common data science questions. Be ready to explain your thought process clearly, as communication is key when working with cross-functional teams.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for curious and technically sharp individuals. Your next big opportunity could be just a click away!
We think you need these skills to ace Data Scientist in London
Some tips for your application 🫡
Show Your Curiosity: We want to see your passion for data science! In your application, highlight any projects or experiences that showcase your curiosity and problem-solving skills. Let us know how you've tackled real-world problems with data.
Be Clear and Concise: When communicating your experience, keep it simple and impactful. We appreciate clarity, so avoid jargon and focus on how your skills in Python, R, or machine learning can contribute to our team.
Tailor Your Application: Make sure to customise your application to fit the role. Mention specific projects or achievements that align with the responsibilities listed in the job description. This shows us you’ve done your homework!
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. Don’t miss out!
How to prepare for a job interview at ENI – Elizabeth Norman International
✨Know Your Data Tools
Make sure you brush up on your skills with Python, R, or any other data tools mentioned in the job description. Be ready to discuss specific projects where you've applied these tools, as this will show your technical prowess and hands-on experience.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled real-world problems using data science techniques. Think about the challenges you faced, the methods you used, and the impact of your solutions. This will demonstrate your analytical mindset and ability to deliver results.
✨Communicate Clearly
Practice explaining complex data concepts in simple terms. You might be asked to present your findings to stakeholders who aren't data-savvy, so being able to communicate effectively is key. Use analogies or visuals if it helps clarify your points.
✨Collaborate and Innovate
Be prepared to discuss how you've worked with cross-functional teams in the past. Highlight any innovative tools or processes you've contributed to, as this shows your willingness to collaborate and improve ways of working within a team.
