Data Scientist

London

Applications have closed

Checkout.com

Boost your acceptance rate, cut processing costs, fight fraud, and create extraordinary customer experiences with Checkout.com's payment solutions.

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We're Checkout.com 
Checkout.com is one of the most exciting and valuable fintechs in the world. 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, Binance 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 number 9 on the Forbes Cloud 100 list and on Glassdoor’s list of Top 10 fintechs to work for. 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. So, join us to build tomorrow, today.
About the Role
Checkout.com is looking for a data scientist to work on the research and development of Machine Learning (ML) models for fraud detection and other business problems. These algorithms will be deployed to provide near-real-time transaction risk predictions, which Checkout.com’s merchants use to make smart payment routing decisions based on their risk appetite.You'll join an enterprising team of data scientists and engineers who are working to deliver fraud detection ML models at scale. Your work will significantly move the needle within a product area that has high strategic importance to Checkout.com.

Key Responsibilities:

  • Work with distributed computing technologies (e.g. Spark, Dask) to: conduct exploratory analysis to test hypotheses, engineer ML features, and train/evaluate ML models.
  • Design, implement and interpret experiments to produce practical insights and improve model performance.
  • Write high-quality Python for feature engineering and model training.
  • Drive the collection of new data and enrichment of existing data sources.

About You:

  • At least 2 years experience developing machine learning models to solve business problems.
  • Strong understanding of: machine learning, probability and statistics.
  • Experience applying scientific methods and thoughtful experimental design.
  • Able to write high quality Python code.
  • Experience with SQL databases.
  • Experience working with Jupyter Notebooks.

Nice to have:

  • Experience in fintech and/or payments.
  • Familiar with distributed general-purpose cluster-computing (e.g. Spark, Dask, Hadoop).
  • Experience with Docker.
  • Experience with AWS or at least another common cloud platform (GCP/Azure).
  • Familiar with the unix shell and shell scripting (for automating tasks).

#LI-GW1
What we stand forAt Checkout.com, everything starts with our values, including the experience we offer our people. #AspireWe supercharge your professional growth with career development programs and leadership training. You can learn your way, with tailored pathways and online platforms. And be inspired at relevant conferences. #ExcelWe don't stop at 'good' here. We strive for excellence amongst our teams every day and recognize colleagues who take it to the next level through our quarterly peer-nominated Hero awards. #UniteWe're proud of our global connections and inclusive environment. So we champion this through our colleague-led community groups and celebrate many cultural events together. Want to see us in action? Take a peek inside here. More about Checkout.comWe empower businesses to adapt, innovate and thrive with the connected payments they deserve. Our technology makes payments seamless. We provide the fastest, most reliable payments in more than 150 currencies, with in-country acquiring, world-class fraud filters and reporting, through one API. And we can accept all major international credit and debit cards, as well as popular alternative and local payment methods. Checkout.com launched in 2012, and we now have a team of 1000 people across 17 international offices. To date, we’ve raised a total of $830 million, with our recent Series C valuing us at $15 billion. We believe in equal opportunitiesCheckout.com is an equal opportunities employer. We welcome applications from all members of society irrespective of age, sex, disability, sexual orientation, race, religion, or belief. We make recruiting decisions based on your experience, skills and personality. We believe that employing a diverse workforce is the right thing to do and is central to our success.

Tags: APIs AWS Azure Docker Engineering Feature engineering FinTech GCP Hadoop Jupyter Machine Learning ML models Model training Python Research Spark SQL Statistics

Perks/benefits: Career development Conferences Flex hours Flex vacation Team events

Region: Europe
Country: United Kingdom
Job stats:  10  1  0
Category: Data Science Jobs

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