Description

Required Qualifications:

• 6+ years of experience delivering data science projects for financial institutions (banking, payments, cards, lending, or similar regulated environments).
• Python — mandatory: Expert, production-level proficiency for data science and engineering (e.g., pandas, scikit-learn, and standard ML/data tooling).
• SQL — mandatory: Advanced proficiency working with large relational/analytical datasets, including performance-aware query design.
• Demonstrated ownership of end-to-end delivery — from problem framing through deployment — with measurable business outcomes.
• Experience leading or mentoring a team and managing delivery against client or stakeholder commitments.
• Strong communication skills; able to engage senior stakeholders and explain technical concepts clearly.
• Bachelor’s or master’s degree in computer science, Statistics, Engineering, Mathematics, or a related quantitative field (or equivalent practical experience).

Preferred Qualifications:

• AWS (cloud) — preferred: Hands-on experience building and deploying data/ML workloads on AWS (e.g., S3, Glue, EMR, Redshift, SageMaker, or equivalent services).
• Direct experience in the payments ecosystem (issuers, acquirers, networks, or merchants) and familiarity with transaction-level data.
• Experience with modern data engineering practices: orchestration, data modelling, CI/CD, and large-scale distributed processing (e.g., Spark).
• Exposure to MLOps, feature stores, and model monitoring in production.
• Prior consulting or client-facing delivery experience

Key Skills

Education

Bachelor's or Master's degrees