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- Tasks: Lead a talented team to innovate in payment intelligence and manage machine learning models.
- Company: A leading global payment company with a focus on innovation.
- Benefits: Competitive compensation, hybrid working options, and career growth support.
- Why this job: Make an impact in the payment industry while mentoring and developing your skills.
- Qualifications: Strong experience with Python and SQL, plus a passion for mentoring.
- Other info: Join a supportive environment that fosters professional development.
The predicted salary is between 43200 - 72000 £ per year.
A leading global payment company is seeking a Data Science Manager to lead a talented team and drive innovations in payment intelligence. You will oversee the lifecycle of critical machine learning models and translate complex data challenges into actionable goals.
Ideal candidates will have strong experience with Python and SQL, alongside a passion for mentoring and technical development. This role offers competitive compensation, hybrid working options, and a supportive environment for career growth.
Data Science Manager — Payment Intelligence (Hybrid) in London employer: GoCardless
Contact Detail:
GoCardless Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Manager — Payment Intelligence (Hybrid) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the payment industry on LinkedIn or at meetups. We can’t stress enough how personal connections can open doors that applications alone can’t.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio of projects, especially those involving Python and SQL, make sure to highlight them in conversations. We want to see how you tackle real-world data challenges.
✨Tip Number 3
Prepare for the interview by brushing up on your machine learning knowledge. We recommend practising common scenarios you might face as a Data Science Manager, so you can confidently translate complex problems into actionable solutions.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace Data Science Manager — Payment Intelligence (Hybrid) in London
Some tips for your application 🫡
Show Your Passion for Data: When writing your application, let your enthusiasm for data science shine through! Share specific examples of how you've tackled complex data challenges and the impact it had on your previous projects. We love seeing candidates who are genuinely excited about the field.
Highlight Your Technical Skills: Make sure to showcase your experience with Python and SQL prominently in your application. We want to see how you've used these tools to drive innovations in your past roles. Don't just list them; tell us how you applied them to solve real-world problems!
Mentorship Matters: As a Data Science Manager, mentoring is key! In your application, mention any experience you have in guiding or developing others. We value leaders who can inspire their teams, so share your approach to fostering growth and collaboration.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to provide all the necessary details in one go. Plus, we love seeing applications come through our own platform!
How to prepare for a job interview at GoCardless
✨Know Your Data Inside Out
Make sure you’re well-versed in the latest trends and technologies in data science, especially around payment intelligence. Brush up on your Python and SQL skills, and be ready to discuss how you've applied them in real-world scenarios.
✨Showcase Your Leadership Skills
As a Data Science Manager, you'll need to demonstrate your ability to lead and mentor a team. Prepare examples of how you've successfully guided teams in the past, focusing on your approach to fostering technical development and collaboration.
✨Prepare for Technical Questions
Expect to face technical questions that assess your problem-solving abilities and understanding of machine learning models. Practice explaining complex concepts in simple terms, as this will show your ability to translate data challenges into actionable goals.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the company and the role. Inquire about their current projects in payment intelligence or how they support career growth within the team. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.
