Senior Consultant - AI Consulting

Engage with banking clients to identify AI-driven opportunities aligned with their strategic objectives. Lead workshops and assessments to craft tailored banking AI solutions in areas such as recommendation mechanisms, process automation, predictive analytics, personalization, and risk management. Translate complex AI concepts and frameworks into actionable business strategies and present findings to senior stakeholders. Architect AI solutions leveraging Finacle s capabilities, integrating technologies like machine learning, natural language processing (NLP), computer vision, deep learning, and Gen AI. Collaborate with product and technical teams to develop banking-related AI/ML use cases, PoCs and scalable implementations. Ensure delivery excellence through robust planning, execution, and post-implementation reviews. Support account teams in pre-sales activities, including proposals and solution demos. Evaluate, develop, tune, validate, and deploy AI/ML models that address complex business problems in the banking sector. Design and implement end-to-end data pipelines, including data preprocessing, feature engineering, model training, and deployment in cloud environments. Leverage cloud platforms such as Azure, AWS, and GCP to deploy and operationalize AI models, ensuring scalability and reliability. Create AI/ML based solutions tailored to the banking industry, such as fraud detection, credit scoring, document processing, and customer service automation. Interface with clients to understand business challenges, design and propose AI solutions and use cases, ensuring alignment with business goals. Experience: 5-10 years, with 2-3 years of dedicated experience with AI/ML solution development, implementation and/or management. Consulting experience is an added advantage. Expertise in machine learning (supervised, unsupervised, reinforcement learning), deep learning, NLP, GenAI models etc. and ability to work with implementation teams to build and train working versions of these models. Sound understanding of cloud-based AI/ML platforms and services (e.g., AWS SageMaker, Azure ML, Google AI Platform) is a plus. Proficiency in programming languages (Python or R) and related frameworks (TensorFlow, PyTorch, LangChain etc.). Proficiency and hands-on experience in deploying and operationalizing AI/ML models in cloud environments, managing model pipelines, and optimizing model performance post-deployment is a plus. Implementing validation and testing strategies for model performance such as white-box testing and black-box testing including unit tests, component tests, integration tests, system tests, performance tests, regression tests, and acceptance tests. Ability to conduct PoCs and guide implementation teams on data analysis, data preprocessing, and modeling to identify and extract valuable insights