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Skills for deploying data science solutions
The role of a data scientist is evolving. And it's now more important than ever, that data scientists know how to deploy and scale their solutions for use across the wider organization. So, as a data scientist, how should you prepare yourself to confront these challenges? Which skills should you embrace and develop, versus which should you suggest are better suited for a dedicated data engineer or software developer?
The data science workflow
The data science workflow involves more than just fitting models. The problem needs to be appropriately framed, a good amount of effort needs to be spent on obtaining and preparing the data, and even after the modelling solution has been developed, there is still a piece of work around deploying and making the solution ready for use.
Taking a closer look at data skillsets
We recently published a post including our take on the Data Scientist Development Pathway. And while that post did highlight various skills over a range of data analytics roles, we thought it would be worth making some more specific call-outs on the types of tools, language, technique and methods data analytics professionals commonly leverage.
Data science roles and skills within your organization
The rapid growth in data science has bought with it an explosion in related roles and job titles. Not only that, but as the career ages, so too are the distinctions of seniority and experience for those in data related roles.
Advanced analytics for leadership
Successful use of advanced analytics is not only up to the data analysts, data engineers, and data scientists. Leadership have a crucial role to play in providing the correct guidance and influence to their data analytics teams. Ensuring they remain focused on identifying and solving problems which are most leveraging to creating and maintaining a competitive advantage over their peers.
What is a Citizen Data Scientist?
You don't need to be a Data Scientist or have Data Scientists in your organization to start leveraging advanced analytics. In-fact, Gartner has even gone as far as defining the role of a 'Citizen Data Scientist', but what does that mean exactly?