About this role
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.
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.
Educational qualifications
- Minimum Qualification Required: B. Tech/MBA from a recognized Tier-1 institute
- Certifications Required: AI Certifications
Work experience
- Total Number of Years of Work Experience: 2+ years
- Relevant Number of Years of Work Experience Required: 2+ years in Python development, including hands-on AI/ML delivery
- Special Call Outs on the Nature of Work Experience: Hands-on experience building Python solutions and AI/ML models for data-driven business or finance use cases; exposure to client-facing delivery and process improvement is preferred.