Skills required for Social Data ScienTists

Social Data Science is an emerging field focused on social good. It’s an interdisciplinary profession where various skills-sets, knowledge proficiency and professional expertise come together. I consider that connected nature of the society due to the internet and increasing computation capacity of the computers has allowed us to look at traditional Social Sciences differently. Additionally, the complex nature of Social Sciences makes it even more exciting. Then the obvious question is, what are expectations from such professionals, I call them Social Data Scientists. This article will try to answer these questions.

TECHNICAL SKILLS

Data Science, in general, is a sub-domain of the technology. Therefore, a minimum level of technical skills is the requirements. Technical expertise may vary according to the organization, position you are serving at, and other available skills sets. Having said that, I consider following are the few of the skills sets which are required.

Understanding of the Databases (SQL, No-SQL), SQL and data extraction

As this domain deals with the large-scale data. It would be best if you had necessary know-how of Database design, normalization and data flow. In addition to that, data extraction fundamentals required to know. You may need to write the queries to dig out the data, and therefore any Structured Query Language is essential.

Good coding experience in general, Python/R in particular

Data Analysis and Statistical modelling implementation need extra-ordinary coding skills. Previous experience with any coding language is desirable. Currently, Python and R are the known Data Science languages, and therefore experience with these specific is becoming a necessity.

Understanding of the Software Engineering (Design, Development, Deployment)

Individuals coming with the end-to-end life software development cycle will be able to deliver better. It makes them easier to see the larger pictures. Somebody with the enterprise-level software development will always have the upper hand. Professionals should also have a good understanding of the Dev-Ops, delivery and deployment.

DOMAIN EXPERTISE

Social Science is vast in itself. It is rooted in its context. If we take Education then, it surely needs the pedagogical understanding and cognitive theories in Psychology. But it cannot be visualized without the Sociology, Philosophy, and Political Science. It’s equally applicable to any Social Science related domain. Now if somebody is interested in working as the Social Data Scientist, then one should have a good understanding of that particular field of work. It is not possible to build models and interpret the future without this expertise.

STATISTICAL MODELS

I am purposefully not merging this point in the Technical Skills. I consider an in-depth understanding of statistical modelling is essential to become a data scientist. Data Scientists keep implementing the statistical models in addition to exhausting the existing models. It demands a good theoretical and conceptual understanding of the Statistical models. Specifically, Social Science researchers will have to focus on this aspect more because they will have to prove the validity and authenticity of the models.

RESEARCH SKILLS

Even though this domain has emerged from Data Science, which is part of the business, it demands academic and research inclination. Professionals should have a good understanding of the research methodologies. Again, research attitude and aptitude are required. One should be inclined to look at any problem critically and from various angles. An individual should have the preparedness to bury oneself below the data for days or at times months to figure out answers to difficult questions. Social Data Science may allow you to collect the data. Therefore, understanding of the Sampling techniques is another expectation.

PROJECT MANAGEMENT

Most of the time, Social Sciences deal with large-scale projects where a lot of respondents are approached. As it is directly connected to a human lot of the permissions are required. Apart from the actual respondents, there are a lot of the stakeholders who are directly and indirectly involved. Considering all these aspects, excellent project management skills become inevitable for Social Data Scientists.

BUSINESS UNDERSTANDING

Social Data Science is the applied research domain. Therefore, application of the fast-paced research using the secondary and primary data is expected. Business perspective can allow understanding what can be end-users’ expectations and requirements. Will they be interested in the findings from this study? It will be even better If results can ultimately be converted into a product or generalized solutions. At least, inventions of the algorithms can be made available to the broader audience, which can take the domain ahead.