Analytics: Ph.D. Not required!

Analytical talent has become the hottest acquisition for companies, and many organizations are scouring for the best talent to bring on board. A question commonly asked is, “Should we hire Ph.D in Statistics or some related field”. The simple answer is, a Ph.D ISN’T required. What is needed for an analyst is a good math background, with some expertise or interest in experimental design.

Quantitative skills are required to understand the reasoning behind the math, but you do not need someone who wants to conduct mathematical proofs. The quantitative skills needed are an understanding of the techniques and their application. Therefore, someone who can understand the math and be able to apply it to their environment is the most essential requisite. Below are some of the degrees or academic fields that could prove useful to hiring an analyst.

1. Mathematics/ Statistics

If you have a math background, then you are probably more than capable, and more importantly, not afraid of any of the math associated with analytics. Math oriented personnel, can easily read about various techniques and learn how to use them quite rapidly. Whether the person has a B.A, M.S. or Ph.D, the math skills are more than enough to take them far. Just make sure the candidate understands that the math is a means to an end, not the end itself.

2. Business or Data Analytics / Data Science

People with degrees in Business / Data Analytics are being groomed for these types of roles. They should have a good strong business sense, along with some very strong quantitative and Information Technology skills, which will make them very versatile. However, the number of universities offering these programs are still small, but growing rapidly. Data Science is very similar and depending on the program could be identical. However, in many cases the Data Science departments will have more theoretical work, as opposed to a business-oriented approach however, both areas are very applicable. Some universities offering this new degree are Hofstra University, Arizona State, Michigan State at both undergraduate and graduate levels.

3. Marketing research

If your organization is heavily focused on marketing, you might find some very good use for people with an advanced degree in Marketing Research.

Quantitative skills are required to understand the reasoning behind the math, but you do not need someone who wants to conduct mathematical proofs.

These folks usually have a strong background in quantitative skills that are very applicable across domains, however, different programs have a varying focus, so its important to understand where the key skills lie, e.g. survey design, customer behavior, etc.

4. Quantitative Finance

Quantitative finance folks are extremely adroit in quantitative methods, and have very strong statistical skills. They understand forecasting and time series models very well, as would be needed in the financial industry. The quant skills here are more than adequate, however, these folks might have some difficulty in some other areas such as marketing, social network analysis, and website analysis. But don’t count them out, hear them out!

5. I/O Psychology or Psychology

If you have a higher level degree in Psychology, especially Industrial Organizational Psychology, you’ve done some real work in the quant field. Not everyone is good at the quant stuff, and not every one wants to do it, but for those that do, this could be a find for your organization. These folks know how to conduct experiments critical for A/B testing, and understand the behavior of customers and can really bring some insight to your organization. If they are real good with multivariate data then that is a big plus. Look for some Ph.D. candidates who may not want to go into academia or who are looking for change from academia. Again, be sure your candidate has a good business sense, it will make all the difference.

6. Science (Physics / Engineering / Computer Science, etc.)

Many folks with a science degree are very goo with quantitative analysis. Candidates in this category can have a wide range of skills, which can include programming, network analysis, multivariate analysis, simulation, etc. Candidates with these degrees are usually very bright, have strong math skills and are very disciplined in their approach to problems. If they are entrepreneurial or have worked in an organizational setting they could be a good match especially if you have problems that are more engineering like, require simulation, or where your data might represent decaying or growth functions like viruses.

Make sure who ever you get has good quant skills, but it is vital that the personality fit within your organization, that the candidate understands, or can understand your business, and wants to be an integral part of the organization.