Manager - Data Analytics and Artificial intelligence

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Address business problems with quantitative solutions like building predictive algorithms / forecasting / scenario simulations etc. Converting a business problem into a quantitative construct, solve it with available statistical / mathematical methods (following the right rigour), engage with IT to implement and finally interpret the outcomes in business language. The range of business problems may cover areas of business growth, improving customer experience, limiting risk exposure, capital quantification, enhancing internal business processes etc.

In this role, you will:

Execute various analyses and develop strategies to support business decisions across the customer’s lifecycle for a particular product/market. Provide support for analytical/strategy projects.

Complete analysis as required and document results and present findings to stakeholders. Execute moderate to complex analysis and strategy with proper instructions.

Identify business problems/new opportunities to drive higher business value. Diagnose and resolve moderate to complex analytical problems

Being part of the IWPB Fraud & Mule analytics team the candidate needs to deliver and deploy suit of capabilities in Money Mule space across markets by designing Money Mule risk typologies across Customer life-cycle stages(Onboarding,Early Stage,Portfolio) by building Anomaly detection models ,rules and graph network solutions .The candidate needs to work closely with multiple stakeholders and teams to drive the solutions to implementation. The candidate should exhibit : Proven expertise in using statistical / ML algorithms for solving diverse business challenges and creating significant business value

Knowledge and exposure to cloud analytics platforms such as GCP, AWS Redshift

Prior hands-on experience in Banking domain and Fraud/Financial Crime tools and platforms will be preferred.

To be successful you will:

Minimum 2 years of experience of using statistical concepts and (or) machine learning models to solve complex business problems. Bachelor’s or Master’s degree from reputed university with specialization in numerical discipline engineering specializations. Understanding of financial-services/ banking-operations preferred.

Good knowledge of programming tools, preferably with proficiency in any one or combination of tools such as SAS, SQL, Big query, Python

Business problem solving skills is essential

Proven expertise in building statistical and (or) ML models for solving diverse business challenges and creating significant business value

Knowledge and exposure to cloud analytics platforms such as GCP, AWS Redshift , Azure etc. would be a plus but not mandatory

Enthusiasm for proactively seeking, exploring and developing use cases for new data and/or tools/wider industry trends.

You’ll achieve more at HSBC

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