Description

You will lead end-to-end data science delivery for financial institutions, owning projects from problem framing through deployment to measurable business outcomes.

This role is on-site.

Responsibilities

• Build production-grade data science and engineering solutions using Python and advanced SQL for large relational datasets.
• Own the full delivery lifecycle, including model deployment, monitoring, and performance-aware query design.
• Lead and mentor a team, managing delivery against client or stakeholder commitments.
• Engage senior stakeholders to explain technical concepts clearly and drive project alignment.

Required Skills

• 6+ years of experience delivering data science projects for regulated financial environments (banking, payments, cards, lending).
• Expert Python proficiency with pandas, scikit-learn, and standard ML/data tooling.
• Advanced SQL skills for performance-aware query design on large datasets.
• Demonstrated ownership of end-to-end delivery with measurable business impact.
• Experience leading or mentoring teams and managing stakeholder commitments.
• Bachelor’s or Master’s degree in Computer Science, Statistics, Engineering, Mathematics, or related quantitative field.

Preferred Skills

• Hands-on AWS experience (S3, Glue, EMR, Redshift, SageMaker) for building and deploying ML workloads.
• Direct payments ecosystem experience with transaction-level data familiarity.
• Experience with modern data engineering (Spark, CI/CD, orchestration) and MLOps practices.

Key Skills

Education

Bachelor's or Master's degrees