Data scientists are the sexier version of statisticians – and one with a better salary. It is somewhat similar to the average software engineer salary – though sometimes higher. So if you are a software engineer you might be wondering whether to take on a new career path in data science. Here are some of the factors that you need to consider if you are thinking about a career change in data science.
No problem if data is not your thing
No doubt that the work is becoming more and more driven by data, so working with it is advantageous in any quantitative career. But still, it is not all about data – if you as a software engineer do not want to spend all your time and effort trying to improve your data skills, you can still have a solid career as a software engineer.
There are plenty of roles for software engineers that do not need data science – think frontend development, infrastructure, and DevOps roles. And they are still in high demand, so if data science is not really your thing, invest your time and effort in gaining expertise and knowledge in what you are interested in.
Think about where you want to position yourself
If you are looking into being an independent contributor, you should pick up a role that best aligns with your interests. But if you want to fit within a company, you need to consider how involved would you like to be with decision-making and business analysis.
As a software engineer, you are closer to the product and your skills are measured on account of how well you make that product in terms of being user-friendly, with better speed, performance, etc. When you progress in your career, you will be expected to manage a team of other engineers or go into a more cross-functional role.
On the contrary, data scientists are more involved with the business side of the organization, as they draw conclusions from data and produce business intelligence that can be helpful in the decision-making process. While software engineers deal more with technology, data scientists are more focused on statistics and interface more often with non-technical teams or stakeholders.
So when you compare both roles, you need to not only think about the specific skill set but also about where you see yourself in the company and which teams you would rather work with. If you prefer to build products and work with other tech people, then software engineer is a better bet, but if you enjoy looking into complex datasets and communicate their significance to non-tech colleagues, you would be better in data science.
Change the game thanks to machine learning
Machine learning is becoming an integral part of many products and blurs the lines between software engineering and data science.
It is a good idea to learn more about machine learning even if you are not looking into becoming a data scientist – especially when it comes to image recognition or language processing.
In conclusion, choose a career path that best suits your strengths and interests. Experiment with different projects and try to interact with various aspects of the business to see where your skills are best fitted in to ensure that you will be able to grow in the long term.