Statisticians provide algorithmic muscle for the machine learning engineer and data scientist’s products. Like most of the careers that are branches of statistics, they are likely to be engaged in extensive data analysis and interpretation, but their work tends to lean more to the mathematical rather than towards software or product development. They are frequently responsible for designing and administering tests, surveys, and polls.
Statisticians are the oldest of the professions involved in the overall data science ecosystem, and most other data science careers are offshoots of statistician or a combination of it and some other discipline.
What You Need To Know About Being – Or Becoming – A Statistician
Because of the field’s maturity, the bulk of the foundation of what you need to know as a statistician will be learned through a good graduate school program. Whatever you chose to learn beyond what is taught in graduate school should focus on make yourself more attractive to whatever type of employer you want to target, either through broadening your skill base or be becoming an even deeper expert in one aspect of statistics..
For example, if you want to work with a company that leans heavily on data scientists, becoming skilled in database systems and learning how distributed systems work will help you design algorithms that can be more effectively used by data scientist to perform their core function; building effective products that serve an organization’s key interests.
In contrast, if you are working for a surveying and polling firm, it helps to dive deeper into some of your core skills. In this case you would want to learn more about designing effective, statistically valid surveys, how to produce effective data visualization to present your results to the wide array of audiences that the polling firm deals with, and how to translate requests from a non-technical audience into methodologies that will allow them to get the answers that they need.
Being a statistician gives you a lot of flexibility but you need to be able to effectively take advantage of it. The particular suite of statistical skills and tools you will need to be most developed in varies considerably across industries and roles. What you need to be an expert in as a pollster will vary from what you will need to be an expert in as someone responsible for at a market research firm, and will vary even more from what you need to know working for a school district.
What You Will Be Doing As A Statistician
Statisticians are responsible for bringing mathematical and scientific rigor to a business or organization’s operations. Much of this will be in the form of designing and managing experiments; businesses need to know whether a particular ad campaign is successful or an efficiency-driving internal change is actually producing results, and a statistician is uniquely skilled and capable of both identifying what needs to be done to make sure that a test is performed correctly without any risk of contamination from other factors and identifying when the best point is to determine if the results are meaningful or not. Designing and performing surveys and polls are just extensions of this experimental focus. They require a similar level of rigor and analytical focus, merely expressed in a different direction.
The specifics of what this mean will vary a lot depending on what sort of company you work for, but the core will be pretty similar, with the mix depending on where you are in the overall cycle for each of your projects. At the start of each project you will spend your time working with stakeholders to ensure that data is collected properly and for the appropriate length of time to ensure statistical validity. In an ideal world, you would wait until the data collection period is finished, and then do a final analysis, but in most business environments you will be expected to monitor how the test is continuing for early signs of success or failure. One the experiment is complete, you will perform your final analysis, identifying potential next steps, if any, and presenting your results to other stakeholders, so that everyone can make informed decisions about what to do with your results and suggestions.
This broadness of the statistician’s education is actually a great advantage. While it is possible to enter into a data science-focused profession from a variety of educational backgrounds, statistics is the best or one of the best choices for virtually all of them. So if you want to shift from being a statistician to a machine learning engineer, for example, simply requires broadening and deepening your skills in software development, while becoming a data engineer requires to become more knowledgeable about database systems. If you like the core work of a statistician, you can move to a more senior position, leading a team of statisticians or potentially becoming a manager or vice president of a group where your statistical skills or mindset would be useful.