Building A Data Science Team As A Nepalese Bank

Infusing the use of programmatic data science for R&D in Nepalese banks is easy.

Take that in with a pinch of salt but here’s a page from the Nepalese private businesses book for the same:

Most data-centric private businesses in Nepal that employ a data science team do not have a team consisting of solely data scientists. In our data science talent market, a business wouldn’t find that many employable data scientists anyway even if they have the budget.

Instead, what has been working well is that these private businesses mostly hire a team lead, who is a data scientist, and the rest are data analysts who are in their second or third year of working in data science.

For banks, setting up an R&D team with the same composition isn’t too hard. Pay a team lead well and get them on the team. Hire programmatical analysts or upskill your current R&D employees to use Python (please not R, you’re limiting your chances of hiring at scale).

That is all you have to do. Give the team room to experiment and a couple of banking experts as advisors, you’ll find the sweet spot between innovation and implementation pretty soon.

Waiting on someone to sell a data science product to you is not a good move. Every other bank buys the same product and the competitive advantage is ever so slightly gained even after spending a ton of money.

Sure, the customers get a lot of value when you buy an off-the-shelf product but how do you personally innovate your approaches as a bank? Already seen this lagging loss of competitive advantage in effect with internet banking.

You've reached the end of this article but there is more!

We're inviting you to the Towards Business Community, a place where first-time founders meet and hold interactive discussions with other entrepreneurs around the globe.

Post a comment

Your email address will not be published. Required fields are marked *