It’s always difficult to make a career shift, especially in a field that’s changing constantly. But if you’re a data analyst who’s looking to make the move to data science, there are a few things you can do to make the transition smoother.
Before we start, let’s discuss the key differences between data analysts and data scientists, and we’ll provide a step-by-step guide on how you can use your existing skills to shift into data science. As you know, both are responsible for working with data, but there are some key differences between the two roles.
What’s the Difference Between a Data Analyst and a Data Scientist?
Typically, data analysts focus on gathering, cleaning, and transforming data. They use this data to create reports and visualizations that help businesses understand their operations and make better decisions.
On the other hand, data scientists go beyond data analysis. They use their knowledge of statistics, machine learning, and artificial intelligence to develop models that can predict future outcomes and in turn, make recommendations.
Steps to Transition from Data Analyst to Data Scientist
First, know what your job will entail
Before you start making any changes to your career, it’s important to have a clear understanding of what your new role will entail. Data scientists typically have a more technical skillset than data analysts, and they’re often responsible for developing and implementing machine learning models. You’ll likely work with platforms such as Microsoft Azure, Google Cloud, AWS, and others to create models and pipelines.
Decide what you want to do
Once you know what becoming a data scientist is all about, you need to decide what you want to do with it. Do you want to focus on general data science, machine learning, deep learning, natural language processing, or something else such as data cleaning, visualization, and stakeholder relations? Answering this question is also another important part of making the move
Now once you’ve decided to leap from being a data analyst to becoming a data scientist, you’ll need to take inventory of your skill set. With that in mind, if you don’t have the necessary skills to become a data scientist, you’ll need to upskill yourself. There are several ways to do this, such as taking online courses on platforms such as Ai+ Training, attending workshops and conferences – such as ODSC events – bootcamps, or getting a master’s degree in data science.
Start taking on projects
Once you know some new skills, it’s time to showcase your newfound knowledge. The best way to do this is by start taking on some projects. The open-source community is a great place to find projects to work on, as are websites such as Kaggle which host a variety of datasets. Projects will help you build your portfolio and showcase your skills to potential employers.
Embrace your background
Don’t forget that you have a lot to offer as a prospective former data analyst. Just because you are taking the leap, doesn’t mean you have to disregard all of the skills you developed. Keep in mind, that you have experience working with data, and you understand the business needs of your organization. So leverage your background to your advantage, and find ways to bridge the gap between data analysis and data science.
Potential employers will likely see the experience as a major plus
Build your network
This cannot be said enough. The importance of building a network in which you can foster positive relationships never gets enough attention. By doing so, you’ll build a group that you can lean on that can help you do everything from finding new projects to work on, or even go so far as to go to bat for you in terms of backing up your skillset.
You can build your network by attending networking events, conferences, and meetups. Get to know people in the data science community, and let them know what you’re up to. LinkedIn is a great place to network too.
It’s clear that transitioning from data analyst to data scientist can be a challenging, yet rewarding experience. By following the steps laid out above, you can increase your chances of making a successful transition. Now if you’re interested in developing the skills you need to make the move in becoming a data scientist, then check out Ai+ Training for cutting-edge data science training. If you want more in-person experience, then the ODSC conferences can help. At ODSC East, Europe, APAC, and West, you’ll enjoy a variety of courses and workshops that can help you build the skills you need to become a data scientist.