The opportunities and challenges of a freelance data scientist
A day rarely goes by when there isn’t an article about how attractive the data science field is for all practitioners, regardless of where they are in their career. According to Glassdoor.com, data scientist topped the list of 50 Best Jobs in America in 2016 and 2017, based on metrics such as job satisfaction, number of job openings and median base salary.
I have worked as a full-time analyst, statistician and data scientist for the past 30 years. Now, while I work towards my master’s degree in business intelligence and analytics, I work full-time as a data scientist with a global telecommunications company. I also teach approximately 10 university-level courses a year, on topics such as statistics, finance, creative thinking and data science.
As well as this, I work as a freelance data scientist for Kolabtree clients. As a freelance statistician I get to select the projects that interest me, set my own hours and work on a variety of different projects in different industries.
The variety is what makes freelancing so interesting and enjoyable. For example, I have helped international publishing journals analyse survey responses from authors and editors. I have also developed analyses for a construction company, developed and analysed heart failure and stroke data and have even worked on biomarker data.
Freelancing gives me the opportunity to work with people from all over the world — for example, I have worked with clients in Italy, India, Amsterdam and Belgium. The variety means I get lots of opportunities to learn about new fields and new techniques. These kinds of learning experiences are vital to providing clients with quality deliverables.
Perhaps the most successful project I have worked on as a freelancer was with a team that was evaluating survey data for an international authors’ journal. The survey had hundreds of questions and results for several thousand authors and editors, who were located in five different countries. I developed smart techniques for analysing such a vast amount of data and the client was delighted with the outcome.
