Mr Odhiambo noted that to lower the cost of hiring data scientists, Blue Nile Analytica has categorised universities into groups where data scientists can be shared.
He adds that data science should be approached as a second degree.
"Some universities have tried training data scientists for four years but that is too expensive and the economy will suffer. We are coming up with short courses of about six months to one year so that we can put them into the job market as quickly as possible."
"Starting with a bachelor's degree straight in data science may not be appropriate for a developing country in Africa," he reckons.
Mr Odhiambo, for example, says that in the US, data scientists are paid $100,000 (Sh12.6 million) to $250,000 (Sh31.5 million) annually. In Kenya, he says the annual pay for a data scientist can even be lower than Sh500,000 a year.
"For you to deliver a hands-driven data science curriculum, you need two professionals; a data scientist lecturer, and the instructor. So for just one class, if you need a competent and certified data scientist, you will be talking about roughly Sh500,000 to Sh1.2 million in one month, on the lower side," says Mr Odhiambo.
"But these professionals are not available, universities do not have the capacity to offer these courses."
The nature of the job data scientists do is what makes them expensive, this is according to data expert Odhiambo. "It is very risky. Also getting security clearance is not easy, also, you are dealing with massive data. Data scientists are expensive because of the amount of money and time invested in training".
Levi Bushuru, a data scientist, notes that companies pay data scientists plenty of money because they are trusted with giving projections for growth.
"Any organisation now depends on data-driven decisions. Every investment needs a survey which comes from data. An investor needs to know if something is profitable or not. Data is very critical in any organisation, and a data scientist is like the backbone of an organisation."
Like Odhiambo, Bushuru agrees that is it highly expensive to train a data scientist because getting the certification is expensive and time-consuming.
"As a data scientist, if I am required to go to a university to teach, I ask them to give me at least Sh600,000 if I have mercy on them. This means they won't afford it," says Mr Bushuru.
Kenya is currently in the budget-making process, Mr Odhiambo says that a good percentage of the budget goes to waste.
He further advises that the Kenyan government should invest in data scientists and train some of its best minds and employ them. "At least one data scientist should be present per ministry and also in county governments. This will help come up with solutions that will track expenses live".
Experts also say that data science is the most sought-after skill in the job market.
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In his experience training corporates, Mr Odhiambo adds that when it comes to data analysis, "corporates do not keep data, they do not know the value of data".
"Data science is the goldmine of the next century, the future is data."
For anyone looking to tap into the data science field, Mr Bushuru advises that data science requires a lot of hard work, perseverance, and sacrifice.
"For instance, the first thing you need is a basic degree in a quantitative field. It also requires someone who is always ready to learn because there is no expert in data science. In data science we don't look at the prestige of those papers, the only thing looked at is the ability to carry out the task," Bushuru.
Bushuru advises that one must be honest if undertaking data science.
In Bushuru's view, data science is new to most people in Kenya. "People are not ready to use data in our country, they wonder what the field entails, most organisations are not ready to use data, yet this data is the one that drives decisions."
Jeovine Kamalah, a data science trainee at Blue Nile Analytica, says that being a data scientist requires commitment and open-mindedness.
"One should find people they can learn from, and develop effective communication skills because there is a reporting stage in every research carried out," Mr Kamalah says his idea for automating things attracted him to the field of data science.