VP, Data Science & ML Strategy

eFinancialCareers; City Of London; On-site; GBP 120,000 - 180,000; Full time

Benefits offered by this job

Health & Wellness

Flexible downtime

Continuous Learning

Job summary

S&P Global Market Intelligence is seeking a Data Scientist Leader to drive the design, development, and operation of high‑rigor analytical and machine‑learning systems across a complex, regulated financial services estate.

The role combines strategy with hands‑on ML engineering to define the AI/ML roadmap, build production‑grade models, and ensure explainability and regulatory scrutiny are met. Collaborate across engineering and product teams to deliver end‑to‑end model solutions.

Qualifications

• Strong experience delivering applied data science and ML in production within regulated environments.
• Deep grounding in statistics, ML, time-series analysis, and predictive modelling.

Responsibilities

• Deliver applied data science and ML in production within regulated financial services.
• Own full model lifecycle: data exploration, feature engineering, model development, back-testing, deployment, monitoring.
• Work with large, imperfect datasets and evolving schemas.
• Design explainable models suitable for regulated environments.
• Monitor production models and manage drift/retraining strategies.
• Collaborate with engineering, data platform, and product teams.

Skills

Applied data science

ML in production

Time-series analysis

Explainable models

Drift detection

Feature engineering

Model deployment

Big data

Tools

Python

Job description

S&P Global Market Intelligence is seeking a Data Scientist Leader to drive the design, development, and operation of high‑rigor analytical and machine‑learning systems across a complex, regulated financial services estate.

The role combines strategy with hands‑on ML engineering to define the AI/ML roadmap, build production‑grade models, and ensure explainability and regulatory scrutiny are met. Collaborate across engineering and product teams to deliver end‑to‑end model solutions.