At a Glance
- Tasks: Build and test machine learning pipelines to influence business decisions.
- Company: Join the Financial Times' innovative Product & Tech team.
- Benefits: Enjoy a flexible 35-hour work week and hybrid working model.
- Other info: Collaborative culture with opportunities for growth and learning.
- Why this job: Make a real impact with your data science skills in a dynamic environment.
- Qualifications: Degree in a quantitative field or relevant data science experience.
The predicted salary is between 50000 - 70000 £ per year.
About FT Product & Technology
Here at the Financial Times, gold-standard journalism is just the beginning. Our Product & Tech team keeps us ahead of the ever-changing digital landscape by delivering cutting-edge products to over one million digital subscribers every day. Our plans for growth rely on a diverse, dedicated and dynamic group of product, tech, delivery and data specialists - everyone’s welcome in this friendly, forward-thinking team.
About The Team
We are an applied data science team where our models and outputs directly impact and shape business decisions and customer behaviour. You will have the opportunity to work on a variety of project types from recommendations to forecasting.
About The Role
This role is an opportunity to develop your data science career and solve challenging problems. A successful Data Scientist would see their work used and applied at the centre of our internal tools, website and apps.
Main Responsibilities
- Building, documenting and testing machine learning pipelines.
- Applying statistical techniques to our web, subscription and content data in order to answer interesting questions.
- Working on solo and collaborative projects.
- Explaining techniques, results and ideas to colleagues, many of whom have not worked with data.
- Advising product managers on experimental design and metrics.
- Sharing your work with the rest of the team, and reviewing the work of other team members.
About You
The below is a list of our preferred competencies and skills for the role. If you do not fulfil every single point, we still encourage you to apply - we’ll review your application and determine whether your unique combination of skills and experience could add something different to the team.
- A friendly and collaborative approach to the people you work with.
- Bachelor or Masters Degree in a quantitative discipline, or intensive data science training (e.g. a bootcamp) or recent experience in data science, machine learning or statistical inference.
- Experience working with large datasets in R or Python.
- A talent for turning analytical results into compelling stories in written, verbal and visual form.
- A practical understanding of machine learning techniques and hypothesis testing.
- An interest in current affairs.
- A fast learner with innate curiosity.
The below are a list of skills which would be a big ‘plus’ but, again, if you don’t have experience with the below that’s totally fine!
- Proficiency in SQL.
- Software development experience.
- Knowledge of the Google Cloud Platform or BigQuery.
- Experience with Airflow.
- Experience in media or a subscription business.
How We Work
We offer a strict 35 hour working week to all staff in our London office. Our hybrid setup means staff are expected to come into the office 2 days a week on average. We operate flexibly and thus this 2 day a week figure should be taken as a general ratio of the time you will spend in the office. Our office is located across the street from St. Paul’s Cathedral and is easily accessible from all corners of London.
Data Scientist in London employer: Financial Times
The Financial Times is an exceptional employer for Data Scientists, offering a vibrant work culture that fosters collaboration and innovation within its Product & Technology team. With a commitment to employee growth, a flexible hybrid working model, and a prime London location near St. Paul’s Cathedral, the FT provides a unique environment where your contributions directly influence impactful business decisions and customer experiences.
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 current or former employees at the Financial Times on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Show off your skills! Prepare a portfolio of your data science projects that highlights your ability to turn complex data into compelling stories. This will help you stand out during interviews and discussions.
✨Tip Number 3
Practice makes perfect! Brush up on your machine learning techniques and statistical methods. Be ready to discuss how you've applied these in real-world scenarios, as this is key for the role.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our dynamic team at the Financial Times.
We think you need these skills to ace Data Scientist in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role. Highlight your experience with machine learning, data analysis, and any relevant projects. We want to see how your skills align with what we do at the Financial Times!
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you’re the perfect fit for our team. Share your passion for data science and current affairs, and don’t forget to mention any unique experiences that set you apart. Let your personality shine through!
Showcase Your Projects:If you've worked on interesting data projects, make sure to include them in your application. Whether it's a personal project or something from your studies, we love seeing how you apply your skills in real-world scenarios.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our friendly, forward-thinking team!
How to prepare for a job interview at Financial Times
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning techniques and statistical methods. Be ready to discuss how you've applied these in past projects, especially with large datasets in R or Python. The more specific examples you can share, the better!
✨Tell a Compelling Story
Data isn't just numbers; it's a narrative waiting to be told! Prepare to explain your analytical results in a way that’s engaging and easy to understand. Think about how you can turn complex data insights into compelling stories that resonate with non-technical colleagues.
✨Collaborate and Communicate
Since this role involves working closely with product managers and team members, practice explaining your ideas clearly and concisely. Show that you can collaborate effectively and are open to feedback. A friendly and approachable attitude goes a long way!
✨Stay Curious and Informed
Demonstrate your interest in current affairs and how they relate to data science. Being able to connect your work to real-world issues shows that you're not just a number cruncher but someone who understands the bigger picture. Keep up with trends in the industry and be ready to discuss them!
