Finding an �effective� data scientist is difficult. Finding people the role of a data scientist can be equally difficult. Note the use of �effective� here. I use this word to highlight the fact that there could be people who might possess some of these data science skills yet may not be the best fit in a data science role. The irony is that even the people looking to hire data scientists might not fully understand data science. There are still some job advertizements in the market that describe a traditional data analyst and business analyst roles while labeling it a �Data Scientist� position.
Instead of giving a list of skills with bullet points, I will highlight the difference between some of the data-related roles.
Consider the following scenario:
Shop-Mart and Bulk-Mart are two competitors in the retail setting. Someone high up in the management chain asks this question: �How many Shop-Mart customers also go to Bulk-Mart?� Replace Shop-Mart and Bulk-Mart with WalMart, Target, Safeway, or any retail outlets that you know of. The question might be of interest to management of one of these stores or even a third party. The third party could possibly be a market research or consumer behavior company, interested in gathering actionable insights about consumer behavior.
Traditional BI/Reporting Professional:
The BI professional generates reports from structured data using SQL and some kind of reporting services (SSRS for example) and sends the data back to management. Management asks more questions based on the data that was sent, and the cycle continues. Insights about the data are most likely not included in the reports. A person in this role will be experienced mostly in database-related skills.
Data Analyst:
In addition to doing what the BI professional does, a data analyst will also keep other factors like seasonality, segmentation, and visualization in mind. What if certain trends in shopping behavior are tied to seasonality? What if the trends are different across gender, demographics, geography, or product category? A data analyst will slice and dice the data to understand and annotate the report. Aside from database skills, a data analyst will have an understanding of some of the common visualization tools.
Business Analyst:
A business analyst possesses the skills of a BI professional and the data analyst, plus they have domain knowledge and an understanding of the business. A business analyst may also have some basic skills in forecasting.
Data Mining or Big Data Engineer:
A data miner does the job of the data analyst, possibly from unstructured data if needed, plus possesses MapReduce and other big data skills. An understanding of common issues in running jobs on large scale data and debugging of MapReduce jobs is needed.
Essential Data Science Skills Every Data Scientist Should Know2
Better yet, who are data scientists? Truth be told, the industry does not have an agreed upon definition of a data scientist. Jokes such as �a data scientist is a data analyst living in the Silicon Valley� are abundant. Below is one such cartoon, just for fun.
