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- Tasks: Develop machine learning models and analyse data to enhance insights.
- Company: Leading financial services company in the UK with a focus on innovation.
- Benefits: Comprehensive benefits package, including pension scheme and medical insurance.
- Why this job: Join a dynamic team and make a real impact in the financial sector.
- Qualifications: Strong statistical knowledge and programming skills, especially in Python.
- Other info: Enjoy hybrid working and solid career growth opportunities.
The predicted salary is between 36000 - 60000 £ per year.
A financial services company in the United Kingdom is looking for a Data Scientist - Statistician to enhance their data insights and models. This permanent role is based in Nottingham with a hybrid working model, where you'll develop machine learning models and perform data analysis.
Ideal candidates should possess strong statistical knowledge and programming skills, particularly in Python.
The position offers solid career growth opportunities and a comprehensive benefits package including a pension scheme and medical insurance.
Data Scientist — ML & Feature Engineering (Hybrid) in Brighton employer: Notjustlabcoats
Contact Detail:
Notjustlabcoats Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist — ML & Feature Engineering (Hybrid) in Brighton
✨Tip Number 1
Network like a pro! Reach out to current employees at the company on LinkedIn. A friendly chat can give us insider info and might even lead to a referral.
✨Tip Number 2
Prepare for the interview by brushing up on your Python skills and statistical knowledge. We should be ready to showcase our expertise in machine learning and data analysis during those tricky technical questions.
✨Tip Number 3
Don’t forget to research the company culture! Understanding their values and mission can help us tailor our responses and show that we’re a great fit for their team.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we can keep track of our applications easily and stay updated on any new opportunities.
We think you need these skills to ace Data Scientist — ML & Feature Engineering (Hybrid) in Brighton
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your statistical knowledge and programming skills, especially in Python. We want to see how your experience aligns with the role of a Data Scientist in our financial services company.
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 you can enhance our data insights and models. Keep it engaging and relevant to the job description.
Showcase Your Projects: If you've worked on any machine learning models or data analysis projects, make sure to mention them. We love seeing real examples of your work that demonstrate your skills and creativity in tackling data challenges.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Notjustlabcoats
✨Know Your Stats
Brush up on your statistical knowledge before the interview. Be ready to discuss key concepts and how they apply to data analysis and machine learning. This will show that you’re not just a coder but also understand the theory behind the models.
✨Python Proficiency
Make sure you can demonstrate your programming skills in Python. Prepare to talk about specific projects where you've used Python for data analysis or model development. Having examples ready will help you stand out.
✨Understand the Company’s Needs
Research the financial services company and their current data challenges. Tailor your answers to show how your skills can directly address their needs, especially in enhancing data insights and models.
✨Ask Insightful Questions
Prepare thoughtful questions about the role and the team. Inquire about the types of machine learning models they currently use or the tools they prefer. This shows your genuine interest in the position and helps you assess if it’s the right fit for you.
