Top 5 Freelance Data Science Jobs
The field of data science is booming and there are more opportunities for data scientists than ever before. Data scientists usually work for large companies, but with an increasing amount of data available, many companies are opening up as a freelance. While the competition for these jobs is high, it’s important to know what you’re getting into when applying.
We’ve compiled this list of the top five freelance jobs in the expansive field of data science with advice from experts on how to successfully land one!
Machine Learning Specialist:
Data scientists need to know everything on this list. Machine learning is the application of algorithms to process problems and generate data. The most successful machine learning specialists work with businesses to discover hidden connections within the data that can help the business make better decisions and predict future outcomes. Many machine learning specialists are working for data science companies, but freelance jobs can be a great opportunity to get your foot in the door of big companies and build a relationship. Once you’ve found success as a freelancer, you can use that as leverage when applying for more permanent positions at those same companies.
Senior Data Scientists:
Senior data scientists have experienced data scientists who can offer a lot of value to companies and other freelancers. They know all the ins and outs, they have strong connections within the industry, and they have a great network of resources. Senior data scientists can help you get your foot in the door, learn new skills or gain access to certain databases and datasets that you might not have been able to access on your own. They’re usually looking for an apprentice who can help them with their projects. Senior data scientists are willing to take on apprentices because they already have established careers and don’t need to work long hours when they could hire an underling for less money.
Business Analyst:
Some data analysts work with businesses to extract useful information from their datasets while other data scientists work to find business insights within the data. In general, business analysts are more marketable than data specialists because they have a better understanding of how businesses function and how those factors influence their decisions. It’s also easier to market the idea that you can help make important business decisions if you have a more business-oriented background. It’s best to have both types of skills on your resume because many companies will be looking for both types of applicants.
Research Scientist:
A research scientist is someone who never got enough sleep in college and has no idea what they want to do when they grow up. They usually have a Ph.D. in one of several different fields, but they have been working on this particular problem for years. They know everything there is to know about their area of study and they think they can conquer the world with their findings. Luckily for you, these people can be quite valuable to companies. A research scientist might be expected to run experiments and collect data for some new statistical algorithm. It’s also possible that you’ll be asked to work on an analytic project that has a secondary function as a research project involving data from a new source or dataset. It’s important to figure this out ahead of time so you can decide if this is the right path for you.
Expert Consultant Freelance Data:
If you want to be an expert in a specific field of data, freelancing is a great way to do it. You can pick up side projects from companies that need help with a specific aspect of their data. For example, if you know SQL inside and out but don’t know anything about python then you could receive requests to work on SQL-related projects. This option might not be the best for people who are just starting or who have varied skill sets, but it can be a great option for someone who is looking to get some experience working with a specific type of data.