Architect AI & Data Science

Description

• Job Summary:

We are looking for a seasoned AI & Data Science Architect to lead and support the Bank's strategic initiatives in AI and Data Science. This role requires a visionary technologist with hands-on experience in designing scalable AI/ML systems, translating complex business challenges into AI-driven solutions, and driving MLOps best practices. The ideal candidate will collaborate across business and technical teams to ensure robust data pipelines, model lifecycle governance, infrastructure scalability, and responsible AI adoption.

Key Responsibilities:

• Architect end-to-end AI and Data Science solutions that ensure scalability, performance, and security. Design robust AI/ML infrastructures, incorporating data pipelines, model training, deployment, and monitoring frameworks.
• Translate business needs into AI strategies and corresponding technical solutions.
• Lead the model lifecycle including design, development, deployment, and monitoring with full MLOps integration.
• Champion MLOps practices such as CI/CD for models, reproducibility, versioning, and model governance.
• Collaborate with cross-functional teamsincluding data engineers, ML practitioners, and domain expertsto align AI initiatives with enterprise objectives.
• Ensure all AI solutions comply with regulatory, ethical, and security standards including explainability and data privacy.

Skills and Qualifications

• 15-25 years of experience in AI, data science, or a related field.
• Proficiency in programming languages such as Python, R, and Java.
• Extensive experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong understanding of data engineering concepts, data warehousing, and ETL processes.
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their AI services.
• Knowledge of big data technologies (e.g., Hadoop, Spark) and data visualization tools (e.g., Tableau, Power BI).
• Proven ability to work with large datasets and derive actionable insights from them.
• Excellent problem-solving skills and a strong analytical mindset.
• Effective communication skills to convey complex technical concepts to non-technical stakeholders.

Leadership & Project Management:

Team Leadership: Ability to mentor and lead multidisciplinary AI/DS teams. Project Execution: Skilled in estimating, planning, and executing technical projects in enterprise environments. Stakeholder Engagement: Strong communication skills to translate business objectives into technical deliverables and act as a liaison between technical teams and business stakeholders.