Data Scientist

Overview:

This role supports the fight against financial crime through the development of a scalable, data-driven Transaction Monitoring (TM) solution. The organization processes over 11 million transactions daily to detect potential instances of money laundering and terrorist financing. As criminal tactics evolve, the TM system must continuously adapt—leveraging advanced analytics, machine learning, and robust data engineering practices.

We are seeking a technically proficient and purpose-driven individual to help enhance and future-proof our TM infrastructure. You will be instrumental in optimizing data processing pipelines, contributing to advanced analytics integration, and ensuring operational excellence in our large-scale monitoring systems.

Key Responsibilities:

• Design, develop, and maintain scalable data processing components using technologies such as Python and PySpark (experience with Azure Databricks is advantageous).
• Conduct in-depth analysis of source and output data to proactively identify data quality or integrity issues.
• Anticipate performance or infrastructure challenges and contribute to long-term technical solutions in collaboration with the engineering team.
• Ensure proper testing, performance monitoring, and documentation of the TM solution.
• Collaborate with platform and DevOps teams to ensure seamless integration and deployment of code into production environments.

Top 3 Focus Areas:

1. Data & Infrastructure Ownership:
2. Take responsibility for large-scale data pipelines and infrastructure, ensuring high code quality, clear design documentation, and adherence to best practices. Mentor junior and medior team members on technical excellence.
3. Cross-Disciplinary Alignment:
4. Drive collaboration between data engineering, IT, architecture, and data science teams to maximize the performance and effectiveness of the TM models.
5. Strategic Stakeholder Engagement:
6. Act as a technical and strategic partner to senior management, providing insights and direction related to TM infrastructure and performance.

Profile & Qualifications:

• MSc or PhD in Computer Science, Data Science, Econometrics, or related STEM discipline.
• 5+ years of experience in software engineering, data engineering, or advanced analytics.
• Proficiency in Python, PySpark, and distributed data frameworks. Experience with Git, CI/CD pipelines, and testing strategies is required.
• Demonstrated capability in designing and scaling big data systems in production environments.
• Strong analytical thinking with a pragmatic, solution-oriented mindset.
• Excellent communication skills in English (written and verbal).
• Deep motivation to contribute to societal impact through the prevention of financial crime.

Ideal Candidate Traits:

• Highly structured and detail-oriented.
• Comfortable operating in dynamic, high-stakes environments.
• Proactive, communicative, and collaborative across diverse teams.
• Business-aware with strong problem-solving and critical thinking skills.

Mission Impact:

Join a purpose-driven team where your technical skills contribute directly to safeguarding the integrity of the financial system. Help shape and enhance an evolving analytics ecosystem designed to detect and prevent financial crime at scale.