<gh-intro>
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We are looking for an ambitious Data Scientist to join our Fraud and Payments team and help us convert every order across all of our business lines by detecting potential fraudulent behaviour and optimizing the payment lifecycle.
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</gh-intro>

<gh-about-us>
  <title>About us</title>
  <text>
With over 200 million users in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people.

We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, national origin, age, or ability.

Our ultimate goal is to make cities for people, not cars. And we need your help on this mission!
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</gh-about-us>

<gh-role-detail>
  <title>About the role</title>
  <text>
You’ll be working in the Fraud and Payments team, which is responsible for processing 1% of all card transactions in Europe. This team is a cross functional team consisting of product managers, data analysts, software engineers and data scientists. Our engines inspect every order across all of our business lines to detect potential fraudulent behaviour and optimize the payment lifecycle - preventing financial losses due to fraud, optimizing payment costs and helping our users to successfully complete their payments. 
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</gh-role-detail>

<gh-responsibilities>
  <title>Main tasks and responsibilities:</title>
<bulletpoints>

• <point>Working with a technical stack consisting of Python, Docker, SageMaker, Airflow and Databricks</point>
• <point>Building and improving fraud prediction models using different predictive approaches</point>
• <point>Exploring techniques that can improve the way we manage payments, including Causal and Reinforcement Learning</point>
• <point>Handling the entire lifecycle from project conceptualization and notebook prototyping to productizing and maintaining a machine learning based solution or other automation that might be serving hundreds of millions of users in production</point>
• <point>Leveraging our in-house data and model platform that allows you to launch new projects in a matter of days</point>
• <point>Deploying and A/B testing solutions for millions of users, enabling fast feedback and measurable added value to customers</point>

</bulletpoints>
</gh-responsibilities>

<gh-requirements>
  <title>About you:</title>
<bulletpoints>

• <point>Exceptional knowledge of machine learning algorithms, statistical inference, and autonomous decision-making systems</point>
• <point>Enthusiasm to collaborate with different roles in product, analytics and engineering to identify problems, explore trends and untap growth opportunities</point>
• <point>Passion for continuous learning and a collaborative mindset, valuing open technical discussions and peer-to-peer knowledge sharing</point>
• <point>Mastery in Python and SQL</point>
• <point>Previous experience in fraud detection, payment optimization or related financial services is a plus</point>
• <point>Strong academic background in a quantitative field</point>

</bulletpoints>
  <text>
Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying!
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</gh-requirements>

<gh-perks>
  <title>Why you’ll love it here:</title>
<bulletpoints>

• <point>Play a direct role in shaping the future of mobility.</point>
• <point>Impact millions of customers and partners in 600+ cities across 50+ countries.</point>
• <point>Work in fast-moving autonomous teams with some of the smartest people in the world.</point>
• <point>Accelerate your professional growth with unique career opportunities.</point>
• <point>Get a rewarding salary and stock option package that lets you focus on doing your best work.</point>
• <point>Enjoy the flexibility of working in a hybrid mode with a minimum of 3 days in the office each week to foster strong connections and teamwork.</point>
• <point>Take care of your physical and mental health with our wellness perks.</point>

</bulletpoints>
  <text>*Some perks may differ depending on your location and role.</text>
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