Data Scientist (Card Payments and Spark)
Fraudio is a fast-growing VC backed payment fraud detection company founded by online payment and AI/ML experts. Our mission is to disrupt the industry by connecting all companies in the payment ecosystem to a powerful centralized AI that detects and prevents fraud in real time, creating unrivaled value.
We are a cloud-native product company at heart. We like to experiment and keep up to date with the latest trends, which enables us to choose the best tool for the job. We work in an interesting and cutting-edge field where the wheel has not always been invented yet. We face a lot of technical challenges to deliver low latency predictions for billions of transactions coming from all over the world.
With offices in Amsterdam and Lisbon, Fraudio is a remote friendly company which currently has a hybrid work environment. We are comprised of people from many countries and cultures, which we believe is a strength. We promote transparency, ownership, collaboration, continuous improvement, quality, and having fun while working together.
Fraudio Portugal is seeking an Intermediate Data Scientist with experience in Spark to join our global team. The ideal candidate will have a deep understanding of machine learning and data analysis, and will be responsible for developing complex data models and machine learning algorithms to detect and prevent payment fraud in real-time.
This is a remote-first position that offers the option to work in-person with colleagues at our office in Lisbon. We welcome applications from candidates who are registered in Portugal or are willing to relocate at their own expense. However, please note that we are unable to sponsor non-EU applicants for this position.
- Design, implement, and maintain scalable data models for large and complex data sets related to card payments using Spark, Databricks and other distributed computing frameworks
- Develop and deploy machine learning models to detect and prevent fraudulent activities related to card payments
- Collaborate with software engineers and other data scientists to develop and deploy real-time and batch processing pipelines for the ingestion and processing of card payment data
- Automate the training and performance monitoring of machine learning models
- Communicate technical findings to both technical and non-technical stakeholders and provide recommendations for fraud prevention strategies
- MSc or PhD in Computer Science, Data Science, or a related field
- 3+ years of experience in data science, with a focus on machine learning, statistical modeling, and data analysis.
- Knowledge of distributed computing frameworks such as Apache Spark
- Proven track record of building and deploying machine learning models in production environments
- Proficiency in programming languages, preferably Python and Scala
- Commercial savy and experience with stakeholder management
- Startup mentality with a strong sense of ownership
- Pragmatic and goal oriented — Prefers good solution that works today over perfect solution that may work in one year
- Preferred in-depth domain knowledge in payments and/or fraud detection / AML
- Strong communication and presentation skills