We are seeking an experienced AI Leader to drive the delivery of AI initiatives across our organization. This role requires a unique combination of technical excellence and collaborative leadership—someone who can navigate complex stakeholder environments, work constructively with control functions, and ensure AI projects move from concept to production. The ideal candidate will oversee traditional machine learning operations, advanced analytics, and contribute to our broader AI transformation initiatives across the bank.

Education & Experience:

Master's or PhD in Data Science, Statistics, Computer Science, Mathematics, or related quantitative field

8+ years of experience in data science, with minimum 4 years in leadership roles

Proven track record in banking/financial services industry

Demonstrated experience delivering AI/ML projects through complex governance and approval processes

Technical Skills:

Expert-level proficiency in Python, SQL, and ML frameworks

Deep knowledge of ML algorithms: regression, classification, clustering, time series, ensemble methods

Experience with ML platforms (Dataiku, SageMaker, Azure ML, or similar)

Strong understanding of model risk management, validation frameworks, and regulatory requirements

Experience with cloud platforms (MS Azure)

Leadership & Soft Skills:

Proven ability to build and scale data science teams

Strong collaborative mindset with track record of working effectively with control and governance functions

Results-oriented leader who drives projects to completion despite organizational complexity

Excellent stakeholder management and executive communication skills

Experience presenting to boards, committees, and senior leadership

Strategic thinking with ability to balance innovation and operational excellence

PREFERRED QUALIFICATIONS:

Experience with GenAI, LLMs, RAG architectures, and conversational AI

Experience establishing or improving model validation processes in partnership with second-line functions

Publications or conference presentations in relevant fields

• Opportunities for professional growth and development
• Competitive salary and bonuses
• Comprehensive insurance coverage
• Supportive work environment
• Visa Premium salary card
• Corporate discounts and events
• Additional vacation days
• Discounted education and employee loans
• New cozy studio office in Port Baku Tower 2
• Strong teamwork with Agile principles, regular team buildings and themed events
• Multicultural environment with foreign colleagues sharing their best experiences

AI Project Delivery & Execution:

Own end-to-end delivery of AI initiatives, ensuring projects progress from ideation through deployment with clear timelines and accountability

Remove blockers, manage dependencies, and drive cross-functional alignment to accelerate time-to-value for AI use cases

Establish robust project governance frameworks that balance speed with quality and compliance

Collaborative Model Risk & Governance:

Partner proactively with Model Validation, Internal Audit, and Risk Management teams to build streamlined, efficient review processes

Transform control processes from potential bottlenecks into enablers by fostering early engagement, clear documentation standards, and mutual understanding of objectives

Lead Model Risk Committee and Architecture Committee presentations, ensuring well-prepared submissions that anticipate reviewer concerns

Champion a "compliance by design" approach—embedding validation requirements into the development lifecycle rather than treating them as post-hoc checkpoints

Model Development & Deployment:

Lead development and deployment of AI initiatives across Risk (PD, LGD, EAD models), Marketing (customer segmentation, churn prediction, propensity models), and operational domains

Ensure model performance monitoring, backtesting, and continuous improvement frameworks

Drive adoption of MLOps practices to enable faster, more reliable model deployment cycles

CVM & Marketing Analytics:

Lead Customer Value Management analytics initiatives including customer lifetime value modeling, next-best-action engines, and campaign optimization

Develop sophisticated segmentation and targeting models for marketing effectiveness

Collaborate with Marketing teams on data-driven customer engagement strategies

AI Transformation Initiatives:

Contribute to enterprise-wide AI transformation including RAG-based chatbot development, conversational AI solutions, and GenAI applications

Support transition from traditional analytics to AI-driven decision making across business units

Team Leadership & Development:

Build and mentor a high-performing team of data scientists.

Establish best practices for model development, documentation, and handover processes

Drive "Controlled Democratization" of AI tools across the organization

Technical Infrastructure & Tooling:

Oversee ML platform operations (Dataiku) for batch and real-time model deployment

Collaborate on GPU infrastructure planning and enterprise AI capabilities development

Ensure integration with data warehouse, APIs, and enterprise systems

Stakeholder Management:

Build strong, trust-based relationships with Risk, Finance, Marketing, Compliance, and IT teams

Serve as the bridge between technical teams and control functions, translating concerns and requirements effectively in both directions

Manage relationships with external vendors and consulting partners

Kapital Bank iş mühiti, əlavə fürsətlər və digər vakansiyaları görüntüləmək üçün Kapital Bank Life səhifəsinə keçid edin.

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