Data Science Projects are not Purely Technical

As is well known, data science is highly interdisciplinary and covers fields as wide-ranging as machine learning, statistics, business analytics, and software engineering. But when you are evaluating different data science solutions and providers, remember that data science is not a purely technical discipline. There are a number of soft skills that are also an important part of making your data science projects work. Here are four of them:

1) Communication Skills

When your project is in full swing, you will see that client-facing communication skills matter more than is often expected. In the data science industry, a consultant needs to interact closely with your team. You should look for a supplier with a management consultant’s mindset who will understand & manage your unique business requirements and effectively communicate with key stakeholders. In addition, the supplier you choose should be able to present actionable insights & recommendations in a clear and compelling way. For this, technical skills are essential but not sufficient.

2) Management consulting skills

There are many skills that a highly-qualified management consultant has that data scientists sometimes lack. As mentioned above, a consultant, regardless of their capability, always needs to interact with a client, and for that, some specific language and communication styles are required. The management consultant approach to problem-solving, innovation and business analysis is unique and mostly taught through experience or in business schools. Therefore, the data scientists you work with should have the requisite business training, or experience in a reputable consulting firm. While the former option might be difficult to find, experience shows that working with people who have world-class consulting experience pays off.

3) Agile mindset

Agile project management & delivery is nowadays a globally accepted standard. In nearly all data science consulting projects, the agile software development methodologies are being used. Therefore, the agile mindset and operating within software project management methodologies like Scrum are necessary. This should be something that your supplier has built into the very essence of their consulting.

4) Problem-solving approach

In most data science consulting projects, the business requirements, and project scope impose very tight deadlines. As a result, your supplier should be able to develop practical solutions in close collaboration with project stakeholders. In proof-of-concept projects, this time is limited to about 2–3 months from the project kickoff and final delivery of a minimum viable product. Your supplier should have a proven track record of delivering effective solutions within these pressing time constraints.

Your supplier should be mindful that solutions to business problems need to be simple, practical, and explainable.

If you are looking for a reliable partner to outsource your data science project, please contact us. We would be happy to provide you with a no-obligation assessment of your situation and outline a potential solution.