How Data Science as a Service (DSaaS) can help your business thrive

by Barbora Fuksa Business Development Manager
16 bdfb dsaas for your business 09 2020 blog post

You might sometimes ask yourself: “How do some companies manage to achieve such good results in such a short period of time?” The secret is quite simple—they just know how to use their big data.

Here are some tips on how to systematize your business to obtain the desired results.


If we are talking from a European perspective, then the situation is clear. There simply aren’t enough experts and versed data scientists on the job market to satiate current demand.

One of the approaches we keep seeing with our clients is offering great employee packages and high pay. However, this strategy is difficult in that it doesn’t make you stand out since everyone in search of the best talent takes this route.

Another issue is that companies keep looking for unicorns. These are usually data scientists who have a Ph.D. and are well-versed in all languages and technologies imaginable. And, of course, they have at least 3 years of job experience in the required domain. However, these are incredibly difficult to come by. In many cases, the company might not even need such an elaborate profile, even if they haven’t realized it yet.

The way out of this trap is building internal competencies. Not everyone in your company will be devising algorithms, but they might be good at learning how to purge and prepare data.


If you cannot find those unicorns, hire them externally. Since such experts are in high demand, they tend to be picky and often want to experience different business domains and many projects. This is something that can rarely be had with large well-established businesses that specialize in a specific niche (banking, insurance, automotive). Thus, it makes sense to hire such unicorns externally from smaller companies that offer DSaaS.

An experienced team of data scientists will help analyse, devise, and execute your use cases. At the same time, with a good team set-up, they will help your internal team grow and hone their skills. The know-how can be transferred simply by co-working, or also via dedicated workshops or courses.


If all the above describes your situation aptly, then it only makes sense to further rethink your investment in quality data science. In Western European markets, data science as a service can be costly. So, it is worth looking into places that can offer identical quality with a better-looking price tag.

Nearshoring with us in the Czech Republic is an ideal solution. Your team will be based in Prague, which gives you a significant cost advantage. Yet, for on-site deployments, our data scientists are typically within 1-hour by plane from Western European clients. In the early days of our projects, we spend most of our time on-site with the customer. Then during later stages, we operate more remotely. Collaboration models are endless. Below is just one such illustration of how data science can be provided as a service. The client provides a dedicated product owner who, in turn, delegates to a team consisting of data scientists, BI experts, and individuals with know-how ideas. On the other side, the DSaaS contractor works with a team providing senior experts.

Get in touch, so we can talk about your specific needs!

Data science team structure
We expand to Germany
Profinit established a branch for the DACH region
Due to growing interest in their services in the DACH region, Profinit has announced the establishment of a new entity, Profinit DE in Hamburg.
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