Digital Finance CoE - AI Analyst

Operational:

• Use Python, SQL, and applied AI/ML techniques to analyze finance datasets, build predictive insights, and generate reports that improve client finance operations.
• Configure systems and develop finance solutions that combine automation with machine-learning models to improve data quality, exception detection, and operational efficiency.

Functional:

• Design Python-based automation and AI/ML pipelines for finance use cases using Pandas, NumPy, and scikit-learn for data preparation, feature engineering, model development, and evaluation.
• Develop, test, and deploy RESTful APIs using Flask, Django REST Framework, or FastAPI to integrate Python and ML services with financial systems and third-party applications.

Responsibilities:

Strategic:

• Work with cross-functional teams to identify finance processes suitable for Python automation, predictive analytics, anomaly detection, and AI-enabled decision support.
• Support solution strategies by translating business needs into scalable Python, AI, and ML components aligned with client-service objectives.

Client Interactions:

• Collaborate with global clients to understand finance transformation needs and develop Python-based automation and AI/ML solutions for specific business challenges.
• Explain technical concepts, model outputs, assumptions, and limitations clearly to non-technical stakeholders to support adoption and informed decisions.