If you are a budding data scientist, or you are looking to advance your career in the domain of data science, then you might wonder about its career prospects. What is the growth trajectory? What are the most fulfilling roles and how do you go about charting your career roadmap?
The good news is that the demand for data scientist roles continues to grow, thanks to the emergence of big data, analytics and machine learning (ML). The data scientist role is certainly not new. But it is constantly evolving to suit industry demands and trends.
The modern data scientist is a new breed. An analytical expert, a problem solver and a naturally curious person. Think of it is a combination of mathematics, computer science and trend spotting. Since data scientists have the best of both – IT and business, they are highly sought-after and generously paid.
As the tech trends evolve, so do the opportunities and career paths. How do you make the most of this boom?
To leverage this opportunity, let’s look at the best data science jobs that are trending on job boards and LinkedIn:
The Data Analyst
Much like a detective, a data analyst interprets data and breaks it down into information that is easily digestable and useful for stakeholders. This information has great value, asit can help stakeholders to make well informed, data-driven business decisions.
Your daily responsibilities might include tasks such as :
- extracting data from an SQL database
- using Tableau or Excel at a specialist level
- building basic visualization or reporting dashboards
And more!
The technical skill-set required is diverse and covers the full spectrum of data science. You need expertise in languages such as R, Python, SQL and C.
Asthe name suggests, it is a highly analytical role. So, if logic, numbers and a figure-it-out attitude is your jam, then go for it!
The Data Engineer
When enterprises reach a point where they have vast amounts of big data, they need a data engineer to make sense of it all. The data engineer sets up the infrastructure that the company will need to organize this data.
Typically, the job involves building massive pools for big data. That is, developing, constructing, testing and maintaining architectures like databases and large-scale data processing systems.
As a data engineer, you need to make sure that the architecture supports the core business needs, those of the data scientists and the stakeholders. For this role, strong software engineering skills are more important than ML and core statistics.
The Machine Learning Engineer
The ML engineer has mastered the science of using data to build predictive models. These models are used for automating of processes. These processes can be anything from image classification, speech recognition, market forecasting to software testing.
There is high demand for the machine learning engineer as companies rush in to make the most of the emergent wave.
As an ML engineer, you will need to have the following core skills:
- Computer programming
- Probability and statistics
- Data modelling and evaluation
- Applying ML algorithms and libraries
- System Design and Software Engineering
- ML frameworks
The Generalist
The Data Science Generalist is quite a popular role. Many companies hire for this opportunity to work with a team of data scientists. It is likely that the hiring company needs data science but is not a data company, or may not build data-driven products.
This role demands a combination of data analysis, production code, visualization and more. Some key skills include a working knowledge of big data tools and experience working with data sets. Currently, data science generalists dominate the job market space as there are a variety of niches that require the ‘generalist’ as opposed to the ‘specialist’ profile.
The great thing about being a data science generalist is the breadth of experience. You will get involved in various phases of data science project lifecycle at some point. This gives you great flexibility in terms of a career move, and you can always make a lateral move somewhere down the line when an opportunity comes up.
Many experts believe that it is important to develop generalist skills in combination with specialist skills as you can add more value to your role with this blend.
Last but not least, when searching for your ideal data science job, do read the descriptions thoroughly. Often there is an overlap of skills between roles and ‘data scientist’ is often used as a blanket terminology. If you are preparing for a specific role, going through the job boards will enable you to understand the skills you need to work on.
The post The Best Data Science Jobs for a Fulfilling Career appeared first on Elevano.
source https://www.elevano.com/the-best-data-science-jobs-for-a-fulfilling-career/
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