Data Science Manager — Real‑Time Payments & AI Leadership

GoCardless Ltd; Lisboa; On-site; EUR 55,000 - 83,000; Full time

Benefits offered by this job

Wellbeing & medical cover

Work away scheme

Adaptive Working

Parental leave

Learning Budget

GC Fridays

Job summary

GoCardless in Lisbon is seeking a Data Science Manager within our Payment Intelligence team. You’ll own the full lifecycle of machine‑learning models, partnering with software engineers, product managers and designers to turn ideas into production‑ready code powering our global payment network on GCP and Vertex AI.

Lead and mentor a high‑performing data science team, define the roadmap, and translate ML concepts for senior stakeholders while tackling real‑time fraud prevention and payment

Qualifications

• Experience leading Data Scientists in complex, high-stakes domains.
• Hands-on with Python/SQL to oversee model lifecycles from prototype to production.
• Familiarity with real-time fraud prevention and payments optimization.

Responsibilities

• Manage and mentor a high-performing team of Data Scientists, fostering technical excellence and long-term career development.
• Oversee end-to-end lifecycle of ML models powering real-time payment decisions.
• Shape the strategic roadmap for Payment Intelligence, translating data challenges into high-impact goals.
• Drive cross-functional collaboration to build end-to-end technical solutions from concept to production.
• Influence senior leadership by communicating ML strategy and business value.

Skills

Python

SQL

BigQuery

Leadership

GCP

Vertex AI

Tools

Google Cloud Platform

Vertex AI

Job description

GoCardless in Lisbon is seeking a Data Science Manager within our Payment Intelligence team. You’ll own the full lifecycle of machine‑learning models, partnering with software engineers, product managers and designers to turn ideas into production‑ready code powering our global payment network on GCP and Vertex AI.

Lead and mentor a high‑performing data science team, define the roadmap, and translate ML concepts for senior stakeholders while tackling real‑time fraud prevention and payment