We are seeking a forward-thinking and versatile RPA Developer – Data Scientist to lead the development of advanced analytics, machine learning and intelligent automation initiatives. This role blends traditional data science with low-code automation, GenAI innovation, and AI governance, helping the organization transform both decision-making and operations. The successful candidate will not only build models and automation flows but also contribute to defining our enterprise AI governance framework, policy and risk controls, and secure AI infrastructure.
You will work cross-functionally with departments such as Operations, Finance, Risk, Compliance, Legal, Retail/ Corporate Banking to align AI use with business strategy, ethical standards, and regulatory expectations.

SKILLS/QUALIFICATIONS:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field (Must have)
• At least 3+ years of experience in Automation, Data Science & Machine Learning (Must have)
• At least 3+ years of working experience in the banking domain, with familiarity in financial product data (Must have)
• Proven expertise in developing Power Automate flows (cloud, desktop) and IDP solutions using AI Builder or similar tools (must have)
• Practical experience in GenAI model usage and prompt engineering, ideally with LLMs such as OpenAI or Azure OpenAI
• Hands-on experience with ChatGPT Enterprise and the creation of Custom GPTs tailored to internal business use cases
• Strong programming skills in Python and SQL; experience with model development and automation scripting
• Familiarity with AI governance concepts and experience in defining policies, risk frameworks, or compliance documentation
• Experience with Microsoft Azure ecosystem (e.g., Azure ML, Azure OpenAI) is a plus
• Understanding of version control (Git), DevOps/MLOps pipelines, and secure software development practices
• Effective communication skills to work with business, compliance, and engineering teams
• Strong ethical mindset, analytical thinking, and willingness to drive responsible AI adoption