Becoming a data scientist is relatively a new concept in Kenya that has been gaining a lot of momentum in most firms that deal with large amounts of data and basically any large firm in Kenya.
Data science is a career trajectory that merges statistics, business logic, and programming knowledge.
Scouring through LinkedIn, the social networking site designed specifically for the business and professionals, one notices a rising trend of a much sought-after profession – the Data Scientist.
A report released by the American Statistical Association in 2018, dubbed Data Analysis Skills Report said that in the next five years, 59 percent of organizations will increase the number of positions requiring data analysis skills.
That is not all, according to IBM, annual demand for the fast-growing new roles of data scientist, data developers, and data engineers will reach nearly 700,000 openings by 2020.
Here are a few things you need to do in order to be an established data scientist in Kenya today:
To become a data scientist, you could earn a Bachelor’s degree in Computer science, Social sciences, Physical sciences, and Statistics.
The most common fields of study are Mathematics and Statistics, followed by Computer Science and Engineering. A degree in any of these courses will give you the skills you need to process and analyze big data.
After your degree programme, you are not done yet, because the truth is, most data scientists also undertake online training to learn a special skill like how to use Hadoop or Big Data Querying.
A masters degree is also an added advantage to pursuing a career in data science
Numerous studies show that Python is the most important language to be learned by a data scientist. In fact, in 2019, this sentiment is being insisted upon, as almost 75 percent of the industry, as well as the professionals, are saying that.
Beginners should, therefore, focus on learning Python programming for at least their first six months and interacting with databases.
Then once you have a good understanding of Python and programming in general, you can then start learning other languages like R and Java, then move to machine learning packages.
Obtain an entry-level job
Most companies are often eager to fill entry-level data science jobs. Search for positions such as Junior Data Analyst or Junior Data Scientist.
System-specific training or certifications in data-related fields (e.g., business intelligence applications, relational database management systems, data visualization software, and many more) might help when looking for entry-level data science jobs.
An entry-level job can help you get additional experience and staying relevant to the ever-evolving field of data science by establishing networks within the industry.
Focus on Soft Skills Too
Industry experts say that simply hiring a data scientist is not enough. Managers need to take special care to align business and data teams thus enabling data scientists to be self-sufficient.
Otherwise, they might not get the expected Return on Investment in data science which is a problem almost 80 percent of the companies face.
Some skills a good data scientist should focus on are communication, problem-solving, ability to draw parallels to real-world problems, prioritization, business acumen amongst others.
To keep up with the changing times, most organizations try to hire candidates who have a definite willingness to learn and upskill.
Companies in 2019 are focusing on not just training a single skill but a cluster of skills which will be relevant for a greater number of years.
Some of the skills that are currently picking up are Automation, RPA, Robotics, Cybersecurity, Artificial intelligence, IoT, connected devices, FinTech, Data analytics, and Blockchain, just to mention a few.
Data Scientists job description
While data science projects and tasks may vary depending on the organization hiring, there are primary job functions that tend to be common among all data science positions such as: