Padmi
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Accenture

IT services · management consulting

S&C Global Network-Strategy-MC-Intelligent Asset Management-Consultant

BangalorePosted 1 month ago
Data Science And StatisticsMid-level
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Entity :- Accenture Strategy & Consulting Team:- Strategy & Consulting Global Network Practice:- Financial Services - Banking Title:- Data Science Consultant Job location:- Mumbai About S&C - Global Network :- Accenture Consulting works at the heart of its clients' organisations and helps address their most complex issues As an experienced financial services professional, your market-leading industry, management and technology expertise will provide critical solutions that answer unparalleled strategic, operational, technology and sourcing demands And, in doing so, you'll improve the future of the global financial services industry Accenture serves the world's leading financial services organisations across three industry groups Banking :Retail and commercial banks and diversified financial institutions Capital Markets :Investment banks, broker/dealers, asset-management firms, depositories, exchanges, clearing & settlement organisations Insurance :Property and casualty insurers, life and annuity insurers, reinsurance firms and insurance brokers Develop data & AI strategies aligned with business objectives and industry best practices Collaborate with business stakeholders to understand analytical requirements and deliver actionable insights Data Analysis and Modeling: Apply statistical and machine learning techniques to analyze large datasets Design, develop, test and implement solutions based on business requirements and strategic direction Perform testing of data to check adherence to internal, processes, policies and regulatory guidelines from RBI Develop predictive models and algorithms to extract valuable insights Collaborate with business stakeholders to understand analytical requirements and deliver actionable insights ML Ops: Design the data pipelines and engineering infrastructure to support our clients enterprise machine learning systems at scale Take offline models data scientists build and turn them into a real machine learning production system Develop and deploy scalable tools and services for our clients to handle machine learning training and inference Identify and evaluate new technologies to improve performance, maintainability, and reliability of our clients machine learning systems

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