Jonathan Calmus Datacrunch Global | Data Sciences Director, Former)AXA Singapore | Head of Data Management

Jonathan Calmus is Data Sciences Director for Datacrunch Global, a leading digital transformation service to profit maximize business with ML, Deep Learning, and Optimization solutions. He leads a team of incredibly talented PhD level data scientists and AI experts, Jonathan focuses on helping Datacrunch’s clients grow and transform their businesses with AI-driven value-added consulting services.

He was previously Head of Data Management of AXA Singapore, focusing on implementing all data management activities from data governance to data quality, data modelling, data sciences and AI.

Prior to this, he has held various role within the AXA organization from regional data manager to head of underwriting, head of telematics, chief actuary and regional head of pricing and product.

He has been working in the insurance industry for over 10 years and before joining AXA he used to work in BNP Paribas as regional data manager. Jonathan graduated from the Sorbonne University and from the French National School of Statistics, Economics and Data Sciences (ENSAE), he holds 3 masters, one in data science, one in economy and one in econometrics.

Harnessing Analytics and AI to Transform CRM and SCM

Data, Machine Learning and Artificial intelligence will fundamentally change the way work is performed. Getting insights from data through machine learning plays a key role in accelerating business critical initiatives, such as predicting customer behaviour, automating process, improving customer experience, reducing costs, providing new services, customizing customer interactions, identifying new market trends.

In this new competitive environment how to develop and implement taylormade AI applications in a way that forester a long term growth for companies in the market.

In this session, we will share how companies can build smart AI applications to optimize their key financial indicators:

✓ Developing and implementing end-to-end applications that seamlessly apply machine learning and AI as a business value multiplier in areas such CRM, Supply Chain Management, or automation.
✓Applying cloud-based applications to accelerate the implementation of data sciences products and reduce operational expenses
✓Automating process by leveraging and customizing state of the art models