We spoke to Fredrik Edin, a freelancing Senior Data Scientist, about his career, the challenges he’s faced and his advice for those looking to get started with consulting in the data field.
Fredrik’s story is just one in a series of articles that focuses on the careers and experiences of data professionals across the Nordic region.
After completing a PhD in Computational Neuroscience, where he simulated brain networks related to human memory, Fredrik moved to Sweden’s largest pension consultancy. There he would work analysing funds and structured products. In 2012, Fredrik was promoted to interim General Manager, China, and moved with his family to Beijing.
Having returned from China, Fredrik worked as head of business controlling for biotech pharmaceutics company Amgen. At about the same time, machine learning really started growing. Some of Fredrik’s tasks involved data engineering and data science. During his time there, Fredrik became more and more interested in data driven and machine learning supported decision making.
With this impetus, Fredrik set up Previsio in 2016 and became a freelance consultant, which he has been for the last 5 years, except for a brief stint at consulting firm Codon Consulting. In his role as data engineer and machine learning consultant, Fredrik has worked with a wide range of clients, with a special focus on smaller companies.
“Coming in as consultant to a company, I am often the only data person. As such I become a generalist and I need to be able to speak effectively to various stakeholders, including upper management. Often the first thing I do is to get sat down with like, with like, upper management inside, you know, how do you want to measure your company success in your company, and then try and get make sure that you get a data infrastructure set up in a sustainable way. Other times I come in and formulate a machine learning project, do a pilot to assess feasibility, and prepare for productionizing the product.”
As a recruitment consultant who works with freelancers on a regular basis, I know firsthand that looking for that next project or assignment isn’t always easy. Sometimes, this can be down to a mismatch from the start. We were keen to hear from Fredrik what his process is for engaging a new project.
“The best way would be for me to be able to sit down with the company and then have a discussion, a good discussion about what their needs are, because oftentimes, they don’t know what their needs are. And so they can’t really formulate it and send it to, you know, to a broker company. This is different to regular IT, which is one of the first places where companies get in-house competence.“
For those new to consulting small companies in data engineering or data science, Fredrik has this advice:
“Don’t try and build something that’s perfect from the beginning. Because small companies are constantly changing strategy and direction. Try to make things that you can put into production very quickly, and iterate on them and make them better, you know, as, as requirements become clear. Also be aware that simpler solutions are often better. Finally, you must always be aware that in a small company you will constitute a large part of the company’s expenses, so you need to try to develop cost-effective solutions and be able to motivate your cost.“
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