Model Monitoring & Data Team Lead

Team lead Model Monitoring & Data

The Model Monitoring & Data Team Lead reports to Head of Model Development and is in charge of ensuring the quality of modelling datasets and model monitoring activities in scope of Central Ayvens Model Development team.

• Strategic Data Management:
  Oversee the collection, cleaning, and maintenance of large datasets for model development and model monitoring. Implement best practices for data governance and quality assurance.
• Advanced Data Analysis:
  Conduct advanced analysis and assess the impact of data quality issues on the modelling and monitoring activities. Create data requirements for model development in line with internal modeling standards and regulations. Perform data analysis on collected data, applying correct cleaning techniques. Translate data insights into actionable recommendations for model datasets improvement.
• Model Oversight:
  Lead the continuous monitoring of model performance, ensuring models meet accuracy and reliability standards.
• Model Performance Analysis:
  Conduct in-depth analyses of model outputs and performance metrics. Identify trends, anomalies, and potential areas for improvement, and develop strategies for model recalibration or redevelopment.
• Documentation and Reporting:
  Prepare detailed reports on model performance and risk assessments, presenting findings to senior management and relevant stakeholders.
• Cross-Functional Collaboration:
  
  Collaborate with cross-functional teams, including risk management, compliance, and IT, to communicate model performance and address any concerns.
• Regulatory Compliance and
  
  Risk Management:
  
  Conduct regular audits of models to ensure adherence to internal policies and external regulatory requirements.
• Mentorship and Training:
  Manage and mentor a team of data analysts and data scientists, fostering a culture of collaboration and continuous improvement.
• Continuous Improvement Initiatives:
  Stay informed about industry trends and advancements in model monitoring techniques, integrating new methodologies as appropriate.
• Framework Development:
  Design and implement frameworks for model statistical validation and performance assessment, including key performance indicators (KPIs) and reporting mechanisms.

• Significant experience (7+ years) in model development, model validation, risk management, or a related field, with a track record of managing complex modeling tasks.
• Proven ability to effectively lead and motivate a diverse team, driving performance and engagement.
• Expertise in statistical analysis tools (e.g., R, Python), working with large datasets (SQL), and data visualization software (e.g., Tableau, Power BI). Understanding of Dev Ops and tools (Git, AWS/Azure).
• Strong understanding of statistical modeling and performance metrics. Strong analytical and problem-solving capabilities to interpret complex data and provide actionable recommendations.
• Excellent written and verbal communication skills to convey complex information clearly to both technical and non-technical stakeholders.

• Model development skills
• Data skills
• Project management skills

• Advanced degree (Master's or PhD) in statistics, mathematics, data science, finance, or a related field.
• Knowledge on regulation (CRR / RTS / Guidelines / IFRS
  9)
• English (fluent, spoken and written)

• Capacity to work in an international and diverse environment.
• Positive attitude, good and transparent communication
• Proactive

• Programming models (e.g., Python, R)
• Data analytics/data handling
• Cloud platforms (AWS/Azure)