At a Glance
- Tasks: Build and test machine learning pipelines to drive business decisions.
- Company: Join the Financial Times, a leader in data-driven insights.
- Benefits: Enjoy a hybrid work model, competitive salary, and flexible hours.
- Other info: Collaborative environment with opportunities for professional growth.
- Why this job: Make an impact on customer behaviour with your data science skills.
- Qualifications: Quantitative degree and proficiency in R or Python required.
The predicted salary is between 50000 - 70000 £ per year.
The Financial Times in London is seeking a Data Scientist to advance their applied data science initiatives. You will build and test machine learning pipelines and collaborate on projects that influence business decisions and customer behavior.
The ideal candidate will hold a quantitative degree and possess skills in R or Python.
A hybrid working model allows flexibility with office attendance twice weekly, ensuring a balanced work-life environment.
Hybrid Data Scientist — ML Pipelines & Insights (London) employer: Financial Times
The Financial Times is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London. With a strong commitment to employee growth, you will have access to continuous learning opportunities and the chance to influence impactful business decisions through your work. The hybrid working model promotes a healthy work-life balance, making it an ideal place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Hybrid Data Scientist — ML Pipelines & Insights (London)
✨Tip Number 1
Network like a pro! Reach out to current or former employees at the Financial Times on LinkedIn. A friendly chat can give us insider info and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your machine learning projects. We want to see how you’ve built and tested pipelines, so make it shine!
✨Tip Number 3
Practice makes perfect! Get ready for those technical interviews by brushing up on R or Python. We can help you with resources to ace those coding challenges.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we’re always looking for passionate candidates who fit the bill!
We think you need these skills to ace Hybrid Data Scientist — ML Pipelines & Insights (London)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with machine learning pipelines and any relevant projects. We want to see how your skills in R or Python can contribute to our team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Tell us why you're excited about the role and how your background aligns with our goals at the Financial Times. Be genuine and let your personality come through.
Showcase Your Projects:If you've worked on any data science projects, especially those involving ML, make sure to mention them. We love seeing practical applications of your skills and how they’ve influenced decisions or outcomes.
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 in London!
How to prepare for a job interview at Financial Times
✨Know Your Tech
Make sure you brush up on your R or Python skills before the interview. Be ready to discuss specific projects where you've built or tested machine learning pipelines, as this will show your practical experience and understanding of the tools.
✨Understand the Business
Research The Financial Times and their data initiatives. Familiarise yourself with how data science influences business decisions and customer behaviour in their context. This will help you tailor your answers and demonstrate your interest in their work.
✨Prepare for Collaboration Questions
Since the role involves collaboration, think of examples from your past experiences where you worked in a team. Be ready to discuss how you contributed to projects and how you handled any challenges that arose during teamwork.
✨Ask Insightful Questions
Prepare some thoughtful questions about the role and the company culture. Asking about their hybrid working model or how they measure the success of their data initiatives shows that you're genuinely interested and engaged.
