The High Expectations for Analytics Professionals

If it is still true that “data scientist is the sexiest job of the 21st Century” as Joshua Crawford, a data science, data engineering and artificial intelligence recruiter and the managing director at Proprius Search insists, it has come with very high expectations for any analytics professional. The profession includes a range of denominations going from basic to advanced, and from area of expertise in public service, business/public administration, statistics, technology, and data science. The analytics profession includes a multidisciplinary body of knowledge. Even though we have argued that any analytics project needs a team, some of the expectations placed on individual analytics professionals are that they must know about data and its organizational flow, areas of application for a given project, computer science, statistical methods, model interpretation, storytelling, security, privacy and ethics. In other words, a new Renaissance Individual. 

The demand for analytics professionals is still very high and many universities have increased their offerings of programs at various levels, preparing these types of professionals. Their curricula are designed to give them a dose of technical, analytical, and soft skills. Generally, these programs are offered as Bachelor or Master programs in computer science, information technology, or information systems specializing in analytics. In any case, they have a technology or business background. They need to learn about statistics, programming, data bases, distributed systems, while learning about how to build different types of models, how to make sense of data, how to write reports, how to tell a story, and how to communicate their results.

Most likely they will have many opportunities to have hands-on knowledge of different tools, most will learn Python, R, and machine learning algorithms, how to use SAS® Miner, Forecast Studio, or Viya; and/or SPSS® Modeler, Tableau® or other visualization tools as well as big data technologies such as Hadoop, MapReduce, Spark, etc.. Furthermore, they are expected to be able to quickly learn a new tool if the ones they know are not available.

Analytics Professionals also need to have a strong mathematical and statistical foundation, be good problem solvers and critical thinkers, ask the right questions, explore, clean, transform, and manipulate data, build models that are transparent, non-biased, easily explainable, and implemented. Moreover, they should be capable of translating their results into business language, seeing the big picture, allow for what-if scenarios, and being ready to go back to square-one and start all over again.

They also must be able to work in teams, play different roles, sometimes mentor new members, sometimes learn from senior members, understand and anticipate the threats of network and data security, data privacy, data ethics.

Implications for Government Analytics Projects

Even though it seems that finding people with all those skills is difficult, we have not even mentioned the additional body of knowledge needed to engage in analytics projects within the different levels of government. For each level of government, municipal, provincial, federal, the type of applied projects is completely different. Their mandates, scope, and timespan are all different. In a federated constitutional monarchy, like ours, the federal government deals with policies that affect all Canadians and are developed by the party in power. This means every time that there is a federal election some ongoing projects are on the line. Similarly, the provincial party in power determines the programs and policies for their citizens and some projects are terminated if there is a change in colours after a provincial election. Municipal projects are more stable but can also be affected if new ward members enter the city council.
Access to the data at each level depends on clearance and other regulations. Data governance is a new concept for many departments and agencies. Data ownership is rarely explained. There is a push to move to Open Data as part of the open government initiative. The question is, will data be more available also within departments? Open government is an initiative to make government more accessible to everyone, meaning Canadians and the business community. 

The good news is that there is an Open Government Analytics site which includes access to several datasets. For those analytics professionals who want to acquire expertise working with government data projects this is a good resource.

All levels of government should lobby universities preparing analytics professionals to include some projects where students can explore the data available in the Open Government Site, even though it looks like adding to an already crowded curricula. That way, students will be graduating with some basic understanding of the type of data available to work in government analytics projects. Some may even consider taking a couple of Public Administration courses, as electives.

References

1. GAP – Government Analytics Projects

2. Weldon, D. (2020). What ever happened to the Sexiest Job of the 21st Century? CMS Wire, https://www.cmswire.com/analytics/what-ever-happened-to-the-sexiest-job-of-the-21st-century

3. https://open.canada.ca/en/content/open-government-analytics