Amritangshu Banerjee
I'm Amritangshu Banerjee, a seasoned AI Architect with 14+ years at the nexus of cloud-native engineering and advanced data science.
About
I’m Amritangshu Banerjee, a seasoned AI Architect with 14+ years at the nexus of cloud-native engineering and advanced data science. I translate bold vision into reference architectures and long-term roadmaps that turn data and workflow challenges into scalable as-a-Service solutions. I lead cross-functional teams in operationalizing Generative AI, Large Language Models (LLMs), and rigorously validated Foundation Models across multi-cloud environments, accelerating clinical intelligence, performance analytics, and measurable business impact.
Data is a team sport, and for 14 years I have quarterbacked enterprise-wide Data Strategy and Governance initiatives that transform raw information into sustainable value. I architect cloud-native platforms on GCP, Azure, AWS and Databricks, embedding rigorous Data Product Management and road mapping that unite creators and consumers to accelerate decision-making, elevate product performance and fuel cost-efficient growth. Partnering with C-suite leaders, I build cross-sector bridges that empower organizations to realize the art of the possible with data and scale its impact across their ecosystem, igniting the next chapter of data-driven innovation as Lead Data Partner.
- 14 years' experience
- Joined November 2025
Industry experience
- Financial Services
- Software & Internet
- Professional Services
- Healthcare
- Consumer Goods
- Retail
- Telecommunications
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Work experience· 13 roles
Built the bank's inaugural Data Science function and a big-data Customer 360 platform via data virtualization to unify analytics across departments. Implemented end-to-end ML pipelines delivering real-time, personalized recommendations, boosting digital channel adoption and 15% customer retention. Reduced support query resolution time by 20% by NLP sentiment analysis in virtual banking bot. Led A/B testing and marketing analytics to optimize campaigns, improving ROI.
Led the design and deployment of a cloud-native GenAI & Data platform—integrating RAG ETL Studio, LLM Gateway/Model Guardian, Airflow orchestrated pipelines, dbt analytics on Lakehouse Databricks, MLflow Feature Store, and Kafka event streams; established Data Fabric and Semantic Layer applying FAIR data principles to democratize trustworthy data products enterprise-wide. Directed enterprise-wide MLOps governance, accelerating AI/ML deployments while reducing technical debt. Delivered end-to-end AI/ML solutions for sales forecasting, inventory optimization, commodity risk management, and marketing analytics, achieving up to 20% operational efficiency gains. Partnered with the CDO in federated data strategy, Data Mesh/Data Governance, and platform modernization for cost-efficient growth.
Established and led the bank’s inaugural Data Science function, implementing AI-driven solutions for customer engagement and risk management that elevated data-driven decision-making across the organization. Architected and delivered a big-data-enabled Customer 360 platform via data virtualization to unify analytics pipelines across departments. Engineered end-to-end machine-learning pipelines that delivered real-time, personalized recommendations to accelerate digital channel adoption, driving a 15% increase in customer retention. Cut customer support query resolution time by 20% by embedding NLP-based sentiment analysis into the virtual Banking Bot. Drove A/B testing and marketing analytics model implementation to optimize campaign strategies, resulting in increased campaign ROI.
Education
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