Data Scientist

  • Tempo Indeterminato
  • Milano

Scalapay

Thanks to our innovative BuyNow PayLater payment solution, Scalapay is transforming the way more than 2 million customers buy online and in-store, empowering 5,000+ merchants to give their customers magical shopping experiences.
Being only 3 years old didn’t stop us from becoming a unicorn 🦄 We have raised over $700mln and we did this thanks to a team built around our 4 core values: #createmagic #staycurious #beimpactful #playasateam.
This is where your magic happens. If you love it, Scalapay it ♥
THE MISSION
Scalapay is revolutionizing the way people shop and pay both online and in-store. Our mission is to create innovative payment solutions that provide magical experiences for customers while delivering exceptional value and revenue to our merchants.
There could not be a more exciting time to join our Data & Risk team as we lead the BNPL space in Europe, partnering with the Fashion and Beauty sectors of the market.
You will be responsible for:
– Algorithms and data are the centres of our efforts to automate processes and support decisions across the business.
– As a Data Scientist, your role will focus on building algorithms, as well as advising and mentoring the Data and Risk areas as we grow.
– Guide and help define the data science and data analysis work for the Product team
– Advise and mentor other data scientists and analysts in the Product team
– Perform statistical modelling, correlation analysis and causal inference to understand behaviours inside the Scalapay product
– Measure, test and learn how different product features are used with quantitative approaches such as A/B tests and rollout plans
– This role will give you the autonomy to thrive while being part of a top-notch team of experienced colleagues who collaborate on the challenges surrounding data science.
– You’ll be a confident communicator who is comfortable advising on the best approach to improve business outcomes in the marketing, credit risk, fraud and operations space.
Who we are looking for: 
– Strong Python and SQL experience
– Expertise in training and deploying predictive machine learnt models
– Ability to reason about statistical models, both applied (clustering methods, tree models, etc) as well as theoretical (frequentist methods, etc)
– Experience with PyTorch, TensorFlow, or other neural net frameworks is a bonus
– Solid skills in building and deploying algorithmic models, preferably in the financial services sector
– Ability to scope projects and decompose work into tasks
– Familiarity with Linux-like development stacks, including Git, Kubernetes, etc
– Familiarity with AWS infrastructure (such as S3, Athena, Glue, etc)
– A Masters Degree (preferred) or an undergraduate degree in a quantitative field such as statistics, mathematics, or Computer Science
What we offer:
– Attractive packages based on skills and experience
– International environment with significant challenges to be met every day
– Lots of opportunities to work with a team of industry tech leaders who are focused on delivering products that offer exceptional user experiences
– Personalised support to accelerate your professional growth and take ownership of the products you deliver: we want to help you grow!
– Latest technologies and being encouraged to bring your flair to the role
Recruitment Process:
1) A quick chat with one of our Talent Acquisition team members
2) The first interview with the Hiring Manager to deep dive into your experiences and better understand your motivation
3) A case study to test your hard skills
4) A Meet The Team session where you’ll get to meet different people at Scalapay and see if you’ll fit into our culture
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Want to learn more? Don’t hesitate to explore our Careers website and Careers website, and our LinkedIn, WTTJ, Meritocracy and Glassdoor pages.
Pro tip: send your CV in English 😉
Super Pro tip: we know that application processes can be scary and frustrating but… we look for talent, not people that tick all our boxes.
We believe in the power of diversity: Scalapay is an Equal Opportunity Employer for any minority, disability, gender identity or sexual orientation.

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