বিষয়বস্তুতে যান

Digital Finance CoE - AI Analyst

Overview
KPMG Indiakpmg.comPosted today
Bengaluru, Karnataka, INঅফিসে
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জ্যেষ্ঠতার স্তর
Mid
চাকরির ধরন
পূর্ণকালীন
কাজের অভিজ্ঞতা
2+ years
বিশেষায়ন
Machine learning & AI

Requirements

  • •Minimum Qualification Required: B. Tech/MBA from a recognized Tier-1 institute
  • •Certifications Required: AI Certifications
  • •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.

Key skills

  • Python
  • SQL
  • Machine Learning
  • Pandas
  • NumPy
  • scikit-learn
  • REST APIs
  • Flask
  • Django
  • FastAPI
  • Process Improvement

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.