Your new company

Reputable financial services organisation.

What you'll need to succeed

Technical Experience:

• Machine Learning & Analytics

• Strong experience in developing ML solutions for financial or risk management domains (e.g., credit risk, market risk, operational risk, liquidity, financial forecasting, fraud detection).

• Expertise in statistical modelling, predictive analytics, and supervised/unsupervised ML methods (e.g., regressions, classification, time-series forecasting, clustering, anomaly detection, NLP techniques).

• Data Engineering & Infrastructure

• Demonstrable expertise in building data pipelines for large-scale historical financial datasets.

• Familiarity with big-data and distributed technologies such as Spark, Hadoop, Databricks, or Snowflake.

• Strong SQL and data querying capabilities.

• Competent programming skills (Python mandatory; R or Java/Scala helpful).

• ML Engineering & Deployment:

• Experienced in modern MLOps tools and methods (e.g., MLFlow, Kubeflow).

• Skilled in containerization and orchestration technologies (Docker, Kubernetes).

• Familiar with automated CI/CD pipelines for ML deployment and model lifecycle management.
  Business & Industry Knowledge:

• Deep understanding of banking/financial services industry (especially Risk, Finance, Regulatory compliance).

• Familiarity with regulatory requirements (e.g., Basel III/IV, IFRS9, Stress Testing, Model Risk Management principles).

• Experience dealing with cross-functional stakeholders including Risk Management, Finance, Regulatory Reporting, and Internal Audit.

• Soft Skills & Leadership:
  
  

• Excellent stakeholder management skills, able to influence and collaborate across Risk, Finance, Data teams, IT, and business units.

• Proven leadership ability to build, motivate, and manage highly skilled technical teams.

• Strong communication skills, translating complex concepts into clear explanations for non-technical audiences.

• Comfortable in ambiguous and evolving scenarios, able to rapidly pivot to business priorities.
  Education & Professional Background:

• Master's or PhD in a quantitative discipline (Statistics, Mathematics, Physics, Economics, Computer Science, Engineering).

• 7–10+ years of relevant industry experience with at least 3–5 years in a leading or senior role in ML projects.

What you'll get in return

• Pay rate between €500-€700 per day (subject to experience).
• 6-Month Contract.
• Opportunity to work with a reputable Fortune 100 organisation within the financial industry.

What you need to do now

If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.

If this job isn't quite right for you, but you are looking for a new position, please contact us for a confidential discussion about your career.