Senior Data Scientist

We are seeking a highly motivated and talented Data Scientist to join our growing team. In this role, you will play a critical part in combating fraud and enhancing the security of our platform. You will collaborate closely with Product, Engineering, and Analysts to:

• Develop and deploy cutting-edge fraud detection models: Leverage machine learning, statistical techniques, and cyber security best practices to identify and prevent fraudulent activities.
• Optimize our data and ML infrastructure: Enhance the efficiency and scalability of our fraud detection systems.
• Research and implement innovative solutions: Explore and implement the latest advancements in fraud detection technologies.
• Contribute to team success: Actively participate in code reviews, anomaly monitoring, and technical debt reduction initiatives.
• Empower others: Develop and maintain tools and methodologies that enhance the team's productivity and effectiveness.

About You

• Proven experience: Demonstrated success in solving complex data-driven problems at scale within production environments (experience with high-volume data processing is essential).
• Strong technical foundation: Expertise in Python, SQL, and relevant libraries and platforms. Proficiency in Object-Oriented Programming and strong debugging skills.
• Analytical and problem-solving skills: Ability to analyze data, identify trends, and select appropriate statistical and machine learning models.
• Collaboration and communication: Excellent communication and collaboration skills with both technical and non-technical stakeholders.
• Continuous improvement mindset: A strong sense of ownership and a drive to continuously improve processes and outcomes.
• Experience with SDLC best practices: Familiarity with project management, version control, unit testing, and CI/CD.

Key Responsibilities

• Partner with cross-functional teams to develop and deploy robust fraud detection models.
• Research and implement innovative fraud detection techniques and technologies.
• Optimize data pipelines and ML infrastructure for maximum efficiency and scalability.
• Contribute to the development and maintenance of data science tools and methodologies.
• Actively participate in code reviews, anomaly monitoring, and technical debt reduction initiatives.
• Ensure the quality, accuracy, and maintainability of all developed models and systems.