Building a top data science team

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Gaurav Chaturvedi_DBSAI and Machine Learning are the new buzz words that everyone seems to be fascinated with today. A sprinkling of AI and Machine Learning in project plans, pitchbooks & business plans can almost guarantee and approval/funding.

Most companies today already have staff boasting skills in AI and Machine Learning. But the question is beyond the jargon, do senior stakeholders / VCs really understand what it means and how to effectively implement it?

Most data scientists, quick as they are in building models, struggle to solve real world problems. This makes for a heady concoction of lofty promises, unreasonable expectations and eventually, a lot of disappointment.

As the machine learning juggernaut rolls on, more and more people are required to know it; to use it – as project managers, key stakeholders or as problem solvers. Businesses today need to do more than merely acknowledge big data and analytics. They need to embrace data and analytics and make them an integral part of their company.

And of course, this will require building a quality team of data scientists to handle the data and analytics for the company. Choosing the right members for the team can be difficult, mainly because the field is so new and many companies are still trying to learn exactly what a good data scientist should offer. Putting together an entire team has the potential to be more difficult. As a head of department how do you build the most effective data science team and where do you start?

To discuss this in-depth, Gaurav Chaturvedi, Lead Data Scientist at DBS  will be joining us Seamless Asia  on 20th April. At his roundtable session, Chaturvedi will be sharing some real-life applications and will help you understand reasons for success / failure of these use cases together with building effective Data Science teams.

Chaturvedi is set to join more than 200 other e-commerce, retail and payments professionals speaking at Seamless Asia. For more information, download our brochure here, or go right ahead and register here.

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