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- Tasks: Join our team to develop and optimize Machine Learning models for payment performance.
- Company: Checkout.com is a leading fintech empowering businesses in the digital economy.
- Benefits: Enjoy a hybrid working model and be part of a diverse, inclusive team.
- Why this job: Make a tangible impact in a high-stakes product area with cutting-edge technology.
- Qualifications: 4+ years in ML, strong Python skills, and experience in FinTech required.
- Other info: Collaborate with passionate problem-solvers and unlock your potential with us.
The predicted salary is between 43200 - 72000 £ per year.
Company Description
Checkout.com is one of the most exciting fintechs in the world. Our mission is to enable businesses and their communities to thrive in the digital economy. We’re the strategic payments partner for some of the best known fast-moving brands globally such as Wise, Hut Group, Sony Electronics, Homebase, Henkel, Klarna and many others. Purpose-built with performance and scalability in mind, our flexible cloud-based payments platform helps global enterprises launch new products and create experiences customers love. And it’s not just what we build that makes us different. It’s how.
We empower passionate problem-solvers to collaborate, innovate and do their best work. That’s why we’re on the Forbes Cloud 100 list and a Great Place to Work accredited company. And we’re just getting started. We’re building diverse and inclusive teams around the world – because that’s how we create even better experiences for our merchants and our partners. And we need your help. Join us to build the digital economy of tomorrow.
Job Description
We’re on the lookout for a Senior Data Scientist to join our Acceptance Rates team, working on end-to-end research and development of Machine Learning models to optimise the payment performance of our merchants.
You’ll be responsible for continually improving existing models and identifying new opportunities to apply Machine Learning to solve real world problems, using cutting-edge approaches such as Reinforcement Learning.
The work this team does has a proven track record of moving the needle within a product area that has high strategic importance to Checkout.com, so there’s huge opportunity for tangible impact.
Key Responsibilities:
- You will be expected to make substantial contributions to the research & development of new ML models.
- Advise on where the team should be focusing its efforts to improve model performance.
- Design and implement experiments to produce actionable insights and improve model performance.
- Collaborate with other data scientists and engineers to productionise ML features/models.
- Write high-quality Python for feature engineering and model training.
Qualifications
Must have:
- At least 4 years experience applying ML to solve real-world problems.
- Prior experience in a Financial Services/FinTech business.
- Solid software engineering skills and able to write high-quality Python code.
- Experience in mentoring more junior members of the team.
- Experience applying scientific methods and thoughtful experimental design.
- Experience with Docker.
- Experience with AWS or at least another common cloud platform (GCP/Azure).
Nice to have but not essential:
- PhD/MSc in Machine Learning or other STEM field.
- Ideally some familiarity with reinforcement learning techniques.
Additional Information
Hybrid Working Model: All of our offices globally are onsite 3 times per week (Tuesday, Wednesday, and Thursday). We’ve worked towards enabling teams to work collaboratively in the same space, while also being able to partner with colleagues globally. During your days at the office, we offer amazing snacks, breakfast, and lunch options in all of our locations.
We believe in equal opportunities
We work as one team. Wherever you come from. However you identify. And whichever payment method you use.
Our clients come from all over the world – and so do we. Hiring hard-working people and giving them a community to thrive in is critical to our success.
When you join our team, we’ll empower you to unlock your potential so you can do your best work. We’d love to hear how you think you could make a difference here with us.
We want to set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable. We’ll be happy to support you.
Take a peek inside life at Checkout.com via
- Our Culture video
- Our careers page
- Our LinkedIn Life pages bit.ly/3OaoN1U
- Our Instagram
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Senior Data Scientist - Payment Acceptance employer: Checkout.com
Contact Detail:
Checkout.com Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist - Payment Acceptance
✨Tip Number 1
Familiarize yourself with the latest advancements in Machine Learning, especially in Reinforcement Learning. Being able to discuss recent trends and how they can be applied to payment performance optimization will set you apart during discussions.
✨Tip Number 2
Highlight your experience in Financial Services or FinTech during networking opportunities. Connect with professionals in the industry on platforms like LinkedIn to gain insights and potentially get referrals.
✨Tip Number 3
Prepare to discuss specific projects where you've successfully implemented ML models. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this demonstrates your problem-solving skills.
✨Tip Number 4
Engage with the data science community by attending meetups or webinars focused on ML applications in finance. This not only expands your knowledge but also helps you build a network that could lead to job opportunities.
We think you need these skills to ace Senior Data Scientist - Payment Acceptance
Some tips for your application 🫡
Understand the Company: Take some time to research Checkout.com. Familiarize yourself with their mission, values, and the specific role of the Acceptance Rates team. This will help you tailor your application to align with their goals.
Highlight Relevant Experience: In your CV and cover letter, emphasize your experience in applying Machine Learning to real-world problems, especially in the Financial Services or FinTech sectors. Be specific about your contributions and the impact of your work.
Showcase Technical Skills: Make sure to detail your software engineering skills, particularly in Python, and any experience with Docker and cloud platforms like AWS. Providing examples of projects where you've utilized these skills can strengthen your application.
Express Your Passion for Innovation: In your application, convey your enthusiasm for problem-solving and innovation. Discuss how you have collaborated with teams to develop and implement ML models, and share any experiences that demonstrate your ability to mentor others.
How to prepare for a job interview at Checkout.com
✨Showcase Your ML Experience
Be prepared to discuss specific Machine Learning projects you've worked on, especially those that had a tangible impact. Highlight your experience in applying ML to solve real-world problems, as this is crucial for the role.
✨Demonstrate Software Engineering Skills
Since solid software engineering skills are a must, be ready to showcase your Python coding abilities. You might be asked to solve coding challenges or explain your approach to feature engineering and model training.
✨Discuss Collaboration and Mentoring
The role involves working with other data scientists and mentoring junior team members. Share examples of how you've collaborated in teams and any mentoring experiences you have, emphasizing your ability to work well with others.
✨Prepare for Technical Questions
Expect technical questions related to reinforcement learning and experimental design. Brush up on these topics and be ready to discuss how you've applied scientific methods in your previous work.
