What to expect:
- Design and develop machine learning solutions for online payments financial crime prevention
- Bring state-of-the-art machine learning research into our financial crime prevention practice
- Drive innovation in using alternative data sources for financial crime prevention
- Work closely with operation teams, analyze financial crime patterns, and create and adapt machine learning based financial crime prevention mechanisms while focusing strongly on the customer’s experience and business growth
- Identify and qualify business opportunities and work with business and product teams to ensure machine learning solutions are addressing the correct business needs
- Provide machine learning expertise to support the technical relationship with Paysafe divisions, including solution briefings, proof-of-concept work, and partner directly with product management to prioritize solutions impacting our business performance
- Own machine learning systems end-to-end, from collecting data to deploying in production and monitoring
- Be responsible for the quality and ongoing evaluation of the machine learning systems
- Work closely with product and IT teams to successfully integrate machine learning systems into our products
- Recommend integration strategies, enterprise architectures, platforms, and application infrastructure required to successfully implement a complete solution
- Collaborate with other engineers to build common tools for accelerating machine learning operations internally
To be successful you need to have:
- MSc or PhD degree in Computer Science, Machine Learning, or related technical field
- Minimum 3 years of professional experience in machine learning
- Solid understanding of machine learning fundamentals
- Strong analytical skills
- Proven ability to implement, debug, and deploy machine learning systems in industry
- Experience in at least one of the following deep learning applications: Computer Vision, Natural Language Processing or Speech Recognition
- Familiarity with graph algorithms and graph databases
- Ability to conduct applied research and bring it to production solutions
- Proficiency in Python programing
- Proficiency in SQL
- Experience with Tensorflow/PySpark or another popular ML framework
- Experience working with cloud technology stack (AWS, Azure, etc.) and developing machine learning systems in a cloud environment
- Ability to write high-quality code
- Result oriented team player
- Strong communication skills and excellent spoken and written English