Indirect network effects
The demand for data science talent is growing and with it comes the need for more data scientists to join organizations. While the application of data science is its own field, it is not relegated to one industry or line of business. Data scientists can have an impact anywhere in any organization.
If you are a budding data scientist or are heading down that path, you know that education is the first step. However, outside of the technical curriculum, there are data science skills that transcend any discipline. Practicing and developing these skills will help separate you from the crowd of job applicants and scientists as the field grows.
These skills will not require as much technical training or formal certification, but they are critical to the rigorous application of data science to business problems. Today, even the most technically qualified data scientist needs to have the following soft skills to get ahead.
What is Growth Hacking, by Juanma Varo
In general, these stages do not follow a linear progression from step 1 to 6. Instead, we often have to go back and iterate between the different stages according to the results we obtain. Today, professionals who are dedicated to this discipline are known as Data Scientists.
Data Scientists are professionals, generally with multidisciplinary knowledge, who have the training and curiosity necessary to make discoveries in the intricate world of Big Data. They are able to shape the enormous amount of unstructured data we generate every day and make its analysis possible. They are in charge of identifying potential sources of information, stitching them together and refining the result set; Data Scientists help decision makers move from ad hoc analysis of data to a constant conversation with it.
Data Scientists are charged with finding patterns in the data, making discoveries based on them, and communicating the implications of what they have learned through their analysis to indicate new business opportunities. They advise executives and product managers on the implications of data for products, processes, and decisions.
Mistakes and learnings as a Growth Hacker, by Victor.
Hackathons are a great way to hone data science skills, though they can be difficult to figure out, especially for beginners. Platforms like Kaggle, MachineHack are helping companies hire top data science talent using the hackathon model. Last month, MATHCO.thon concluded its “car price prediction” challenge.
A total of 2,383 data science professionals participated in this experience, of which 50 made the cut. The top three finishers won cash prizes. IIT Madras professor Chandrasekharan Rajendra said candidates should continuously update their knowledge and differentiate themselves by actively participating in international hackathons.
Often when we talk about data science projects, no one seems to be able to give a solid explanation of how the whole process unfolds. From collecting the data, to analyzing and presenting the results. The OSEMN framework covers every step of the data science project lifecycle, from sourcing, cleaning, exploring, modeling and interpreting the data.
What a data scientist does
Security is undoubtedly one of the hottest and most active sectors within the technological landscape. Fortunately, companies and governments are increasingly concerned about the security of their systems or the protection of their users’ data and, in a short time, the sector is starting to demand more and more professionals who are experts in security audits, hacking, vulnerability analysis, attack mitigation…
Cybersecurity is a very active sector, however, how to enter this sector? How to become a hacker? When you ask yourself this question, one of the first answers that comes to mind is that you have to be a bit self-taught, be eager to learn, experiment and spend time documenting and experimenting. Basically, one of the images we associate with this process of “learning to be a hacker” is that of young Matthew Broderick in the legendary 1983 film War Games:
As we commented at the beginning, the desire to learn on one’s own and learning by doing, are two factors that have greatly marked this discipline. However, nowadays, it is increasingly common to find formal training in the field of security, including Master’s degrees, university experts, etc.