Join our Fraud Team in Tallinn, Estonia to protect millions of users, stop fraud in its tracks, and build smarter systems that make online payments safe for everyone!

About us

With over 200 million customers 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, age, or disability.

Our ultimate goal is to make cities for people, not cars, and we need your help to achieve this mission!

About the role

You’ll be working in the Fraud team which is responsible for detecting and preventing payment fraud. Fraud team is a cross functional team consisting of product managers, fraud data analysts, software engineers and data scientists. Our fraud engine is a high load system which inspects every order across all of our business lines to detect potential fraudulent behaviour and financial loss to the company. See what our data science team wrote about How to stop fraud with ML — best practices at Bolt. Furthermore, you will have the opportunity to explore the potential of other projects within our Commerce organization intended at reducing payment costs and enabling our customers to use our services.

Main tasks and responsibilities:

• Working with a technical stack consisting of Python, Docker, SageMaker, Airflow and Databricks
• Building fraud prediction models using different predictive approaches
• Designing and running A/B tests. Interpreting test results and proposing improvements to the Fraud product
• Optimising the models across all our markets to minimise losses from fraudulent transactions while preventing unnecessary friction for regular users
• Handling the entire lifecycle from project conceptualization and notebook prototypes to productizing and maintaining a machine learning based solution or other automation that might be serving thousands of calls per second in production
• Leveraging our in-house data and model platform that allow you to launch new projects in a matter of days
• Working in product feature teams together with data analysts, product managers and software engineers to find and unlock business opportunities in both Fraud and Payments domains. 
• Discussing the problems and technical innovations within the broader data science team that provides a pool of peers and mentors
• Deploy and validate solutions for millions of users, enabling fast feedback and measurable added value to customers

About you:

•  Experience in Python programming, including libraries like Pandas/Numpy/sklearn/OR-tools
•  Experience with Spark/Databricks and writing complex SQL queries
  Experience in applying machine learning algorithms to real world problems
•  Basics of software version control, cloud infrastructure, build and deployment pipelines
•  Understanding and practical experience with statistical hypothesis testing
•  Proactive mindset, willingness to take initiative and work with little supervision
•  Enthusiasm to collaborate with different roles in product, analytics and engineering to identify problems, explore trends and untap growth opportunities
•  Strong verbal and written communication skills in English
• Previous experience in fraud detection, payment optimization or related financial services
• MSc or PhD in a quantitative field

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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GENERAL

Why you’ll love it here:

• Play a direct role in shaping the future of mobility.
• Impact millions of customers and partners in 600+ cities across 50+ countries.
• Work in fast-moving autonomous teams with some of the smartest people in the world.
• Accelerate your professional growth with unique career opportunities.
• Get a rewarding salary and stock option package that lets you focus on doing your best work.
• Enjoy the flexibility of working in a hybrid mode with a minimum of 2 days in the office each week to foster strong connections and teamwork.
• Take care of your physical and mental health with our wellness perks.

*Some perks may differ depending on your location and role.

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