Spatial Career Guide – Spatial Statistician
April 26, 2012
This is my fifth post in the Spatial Career series. In previous posts I’ve written about how to prepare for a career as a GIS Software Developer, as a Geospatial Analyst, as a Cartography/Visualization Specialist, and as a Geographic Information Scientist. In this post I will describe how to prepare for a career as a Spatial Statistician. This career path is similar to the GIScience path in that it’s as critical for you to want to be a statistician as it is for you to want to work with geographical data. So this guide might be reasonably helpful for anyone interested in a career as a statistician (but you’ll want to substitute specifics from the relevant application area and/or data universe, i.e., instead of geographic/spatial you’ll have to find out about the nuances in health, financial, etc). So, here are 5 steps that should put you in good position for a career as a spatial statistician.
Step 1. Get an advanced degree. I would say for this path you really should get at least a Master’s degree and a Ph.D wouldn’t hurt. In fact, one nice thing about the statistician route is that a Ph.D can open up options in private industry as well as in government and academics. Businesses aren’t afraid to hire a Ph.D type for a quantitative position whereas in other roles they will shy away from a Ph.D. So this could be a good option for someone who has a PhD but no longer wants to pursue an academic career. Also, this is another career path where you might consider at least one degree in a field other than geography. Unfortunately the market place is such that people won’t value your degree in geography in terms of the quantitative preparation you would’ve received in school. So I think you have to round out your training, ideally with a degree in math or statistics. There are several combinations that would work. A bachelor’s in math or statistics with a Master’s in Geography would work. A bachelors’ in geography and a Master’s in statistics would probably be better (you would want to minor in math or at least take a full set of courses in Calculus and Linear Algebra as an undergrad). Or, you might consider a joint Master’s in both geography and statistics. This would require some administrative effort and more time but it would be a nice combination and open a lot of doors.
Step 2. Become an expert in spatial analysis methods. Unfortunately, it’s fairly difficult to acquire this type of training. Most geography programs have a few offerings and one or two people on the faculty with appropriate expertise but most programs don’t have enough depth in this area, at least not in my opinion. There are a handful of programs that come to mind where you’ll get all the spatial analysis training you could want and more but they are few and far between. Top on my list is Ohio State because you might get a chance to study with Noel Cressie, who is pretty much the godfather of spatial statistics. He is in the Statistics department where they offer a special program in Spatial/Environmental Statistics but I suspect there are solid ties to Ohio State’s outstanding geography department. Other key programs (and key people) to consider would include UC Santa Barbara (Michael Goodchild), Arizona State (Luc Anselin) and SUNY Buffalo (Peter Rogerson). Each of these programs has a number of talented faculty and an Associate Professor might make a better advisor since they’re a bit less likely to be globe-trotting than the super stars. If you’re Canadian or interested in studying in Canada, take a look at Ryerson University – they offer a good applied graduate program in Spatial Analysis. If you’re in the UK, check out the University of Leeds. There are probably others that I’m leaving out. Feel free to suggest others in the comments section below.
Step 3. Learn the most popular statistical software programs. I would try to obtain some exposure to all of the top statistical software tools including SAS, SPSS and R. The more the merrier. Add Stata and Minitab and others if you can and you might check out free trials of newer technologies like Alteryx. You’ll probably have one go-to tool that you like best but you don’t want to forfeit a job opportunity just because you aren’t familiar with the software the target organization has already licensed. Spend enough time to feel comfortable doing basic analysis in a few different statistical computing environments. You need to be able to get past the gatekeepers in Human Resources who might toss out your resume if it doesn’t have the right buzzwords listed. Also, learn how to automate tasks in these computing environments. Let a scripting language allow you to reproduce results at a click of the button. You don’t need to take hard-core computer sciences classes, not that it would hurt, but some basic programming concepts will certainly help.
Step 4. Learn to communicate effectively. Read bullets 3 and 4 in the GIS Software Developer post and read the Cartography/Visualization specialist post. Being a statistics nerd is cool but don’t be a statistics nerd who can’t communicate with real people. Try to explain things so that a sophomore in high school would be able to understand what you’re saying. And, try to be really good at data visualization. The ability to communicate through visualization, narrative and anecdote is what will set you apart from just the regular statistician who writes equations on the white board when asked to present something to a non-mathematical audience. Instead, help your organization and your clients visualize their data in a way that leads to better understanding and collaboration. For more on this read my post on Geospatial Visualization in Business.
Step 5. Get some applied experience. You will learn a ton of great stuff from your statistics professors and other faculty. They will be able to teach you all about theory and methods. But, when it comes to applying these methods you will want to find a practitioner who has been forced to deliver answers to difficult questions with messy data under tight time constraints (think days or weeks instead of months or years). The rare professor will be good at both but don’t count on such luck. Instead, plan to volunteer to do data entry or whatever you have to do in exchange for the opportunity to interact and learn from statisticians who work on applied problems. Building statistical models that work well doesn’t involve particularly elegant mathematics, at least not in my experience. You have to be able to use a bit of “art” to get some models to work. This doesn’t make the model less useful, it will do the opposite if you do it well, but it won’t be something you can publish in an academic journal and most of your professors won’t like it. You have my permission to ignore them (unless you need their signature on your dissertation or want tenure). Learning how to do a bit of brute force modeling is a great skill to add to your tool belt. It just might allow you to actually suggest a real solution to a thorny problem. And that’s what brings in the big bucks and for some, if you’re like me, the big fun.
The opportunities in statistics/analytics are huge. If you haven’t heard the term “Big Data” by now you’ve been hiding under a rock. Use of the term Big Data may be a passing phase but a world in which all organizations are trying to make sense of enormous volumes of data has just begun with no end in sight.
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A good example of a person in this profession is Dr. Peter Rogerson – SUNY at Buffalo. http://www.acsu.buffalo.edu/~rogerson/
Not much there on the page unfortunately – but someone that has melded statistics and geography in very meaningful ways.
Thanks, Rob! I agree that Peter Rogerson is one of the key figures in this area. And Buffalo may now be the very best program to attend especially if you’re interested in spatial statistics and health, because of a strong faculty including Dr. Rogerson, Jared Aldstadt, Eun-Hye Enki Yoo, and, beginning this fall, Geoffrey Jacquez.
Good article Justin. The timing was good for your mentioning of Alteryx as a tool for spatial statistics. In the current release of Alteryx there is a tool to access R within an Alteryx module. We are currently working on major enhancements in terms of ease of use and reading and writing Alteryx spatial *.yxdb format files into R sp class (spatial) objects that will be coming out in the upcoming 7.1 release of Alteryx. In addition, we are working on PMML based approaches within Alteryx to make integration of statistical model results into business processes seamless.
Dan, thank you for the comment and for the latest on integration with R. Please keep me posted. Is there a free trial or a demo that I could see?
The first set of the enhanced R tools will be part of the 7.1 release which is scheduled for late June. The tools fit into the Alteryx visual programming canvas and aren’t stand alone. What this means is that someone interested in them can trial them as part of a 30 day trial of Alteryx 7.1 when it is released. An initial demo of some of the tools was included as part (the last third) of a recorded webinar describing the new features in Alteryx 7.0. The webinar can be accessed through: http://pages.alteryx.com/Alteryx-7.0-Webinar.html
Closer to the Alteryx 7.1 release, I will be doing a number of preview blogs and video demos for the new R-based tools.
Thanks for sharing these details, Dan! Keep me posted as 7.1 gets closer.
I’m always happy to see articles like this being posted by experienced spatial statisticians and spatial analysts. Assuming that an individual has acquired the necessary education and skill sets, I believe that your most important point is that of being able to communicate effectively – specifically, what does a spatial statistician do? Being able to simplify what many consider to be scary mathematics is a skill set that many scientists have not mastered outside of academia. In industry, supervisors and co-workers need to gain a basic understanding of standard spatial analytical processes. By utilizing appropriate visualization tools, and using metaphors to explain the science side, they can recognize the tangible outputs, and respect what you do. Thanks again for the article.
Thanks, James! I appreciate the feedback!
[…] Analyst, as a Cartography/Visualization Specialist, a Geographic Information Scientist and a Spatial Statistician. In this post I will describe how to prepare for a career as a Geospatial database administrator […]
Hi, Justin. Your articles on spatial careers are the most useful guides I have found.
A few years ago I discovered I have a love and aptitude for mathematics. I also have had an increasing obsession with physical geography and environmental science. My background is in a completely unrelated field, but I’ve started taking the first steps toward a career change by completing some GIS and math classes at the local community college. Your articles really helped orient me to the various geospatial career paths. I’ve been considering focusing on geospatial statistics, and I’m now more than ever convinced that pairing an MS in Geography with a Graduate Certificate in Statistics is the way to go for me. I am fortunate that both programs are offered at our local state university. Thanks for the great information!
Theresa, Thanks for posting the positive feedback – I’m so glad to hear my blog has been helpful! Sounds like you’re making some good moves with coursework and degree planning. Please let me know if there’s anything I can do to help. Best of luck with your career change and please keep me posted along the way.
Hi Justin, thank you. This spatial career guide helps me to decide my career direction. I am a graduate student majoring in GIS, and I am interested in Spatial Statistics. Recently, I started to search for jobs online using key words “Spatial Statistics”, but there are very limited search results. Could you give some practical guide for looking for jobs in this area? Any advice would be appreciated.
Hi May – I’m glad this has been helpful. For statistics type jobs you’re probably better off searching with keywords “statistics” and “GIS” (or geographic, geospatial, etc). Another approach would be to search using your technical skill set; so searching for jobs that involve “SAS”, “SPSS”, “R” and “ArcGIS” or whatever software tools you use. Yet another approach would be to look for jobs with the title “Data Scientist”. Unfortunately, as a geographer, you’ll have to educate most employers as to what you can offer with your GIS/geography training. I’m confident that this area will grow but the term “spatial statistician” may not really be relevant. I think Data Scientist or Geographic Data Scientist is probably more likely to catch on. Good luck! Cheers, J.
Excellent post. I have a B.A/M.A in geography with an emphasis in remote sensing and physical geography. Unfortunately, the job market for my skill set isn’t good. Most remote sensing job posts require security clearance and/or 10 years experience and the environmental science jobs require more of a geology background with multiple certifications. I do have 2 years worth of statistics courses under my belt as well as one calculus course – “Applied Calculus I”. I use statistics all the time and I really enjoy exploring and analyzing datasets using R and SPSS. I have decided that I would like to pursue a career in this field since the applications are limitless. Will a certificate in statistics be enough to land a job or should I take more math courses at a community college?
I think a certificate in statistics would be useful. You’ll want to take more advanced courses than a local community college would likely offer so you might want to look at online offerings unless you have convenient access to a major University. Look for offerings from the Economics department (Econometrics) or the Business School (Applied Regression) as well as the math/statistics department. Another option is to simply train yourself using books and online tutorials to expand your skills using R and SPSS. Sounds like you’re on a great path to becoming a Data Scientist, arguably the hottest career path currently available. Best wishes, Justin
This post is really helpful to me as a statistics practitioner with great interest in GIS. I have printed this post, and keep it for career goal reference.
FYI, Dr. Cressie is moving back to Australia, no longer in OSU.
Glad to hear the post is helpful – thanks! Yes, I had heard the news regarding Professor Cressie. Despite that OSU remains a top program so far as I can tell. Thanks for posting your comments! Cheers, Justin
Hei! great post!
I am an economist with a master in statistics and a passion for spatial data, handling in R. What about spatial econometrics?? Would you suggest some particular path? I´ve done carreer in financial audit and SAP but I do want to switch to spatial analysis….spatial econometrics.
Your best bet would be to study at Arizona State under Luc Anselin, who wrote the book on spatial econometrics. You might also look at UT-Dallas and possibly Buffalo.
Hi Mr. Holman.
This post is helpful to me, thank you very much.
I am an undergraduate of Statistics from a university in Indonesia. I am very interested to further my education if the field of Spatial/Environmental Statistics. I browsed the Spatial Statistics & Environmental Statistics (SSES) program at Ohio State University, it had closed. In a linear master program, do you have any advice for me to continue my education?
The director of the program and the godfather of spatial statistics, Noel Cressie, left Ohio State and moved to the University of Wollongong in New Zealand. He’s set up a similar program there called the Center for Environmental Informatics: http://niasra.uow.edu.au/cei/index.html
That would be a good place to start. Another strategy would be to read some of Cressie’s more recent publications and find where his co-authors work.
There should be more of these types of programs. Maybe there are and I just don’t know about them. Let me know what you find.
Of all the career guides, the spatial statistics career path is the one that interests me the most. My background includes a Master’s of science in geology, GIS certificate completed during masters degree, and 5 years working in the environmental consulting industry. Given my background, are there any practical steps I can take to do work in this field? My plan so far includes: 1) build up my technical proficiency in various GIS and statistics concepts and software (learning phase), 2) look for opportunities in my industry (not much GIS use in my company) that incorporate more GIS analysis, 3) build a portfolio of various projects I’ve worked on (freelance, volunteer, self projects). I also know that gaining some programming proficiency will be important.
I can’t go back for a MS in statistics right now (money and time constraints), but would a statistics certification be something worthwhile to look into (e.g. statistics.com offers online certifications, also there are data science certifications that could be useful).
I think your plan makes some sense but I would start with the programming piece. My advice would be to learn Python and check out the “PySal” module. Maybe get a taste of R too. To me this would be the most efficient path to marketability in the data science world. I wouldn’t pursue any further degrees or certificates but the portfolio idea is good.
Thank you for this simple, yet insightful post. I had my BSc and MSc in Urban Planning in Nigeria. I love to develop a career on GIS Applications. I was able to find a supervisor in Germany, who just believes in me, after I was able to draft a proposal, just simple ideas on GIS Applications to Health outcomes. However, I have no explict background in GIS, Programmming, Statistics, Mathematics or Geography, except basic modules during my studies. I started the PhD on the note that I would take a course on spatial statistics. I have taken the course and I discovered that, it is a different field from my background. After the course, I had redrafted my proposal. But my challenge is that I dont have the expertise required, practical skills etc. I am scared and sometimes I feel like runing away from the PhD program. I found your blog today after typing on google *the required skills to be a spatial statistician*. What is your advice for me? what can I do to overcome this hurdle? Thanks
Thanks for your note. First, don’t feel intimidated by the vast amount of knowledge you don’t have already stored neatly in your brain. That’s why you’re in graduate school, right? If you already knew everything you wouldn’t need a PhD. Second, you don’t need to become an *expert* in spatial statistics to become an expert in “GeoHealth” or GIS + Epidemiology. It’s one important piece of the puzzle but, as you note, there are other equally important pieces including Geography, GIS, programming, specific health outcomes, etc. The only expertise you need to develop is the minimum level sufficient to complete a meaningful research project. And the best way to learn is to figure out what you *need* to be able to do on your own. Don’t think of your PhD studies as a linear sequence during which you first acquire all knowledge necessary to do research and, only then begin said research. You should expect to learn by doing along the way. My suggestion is to break your research proposal into very small, manageable tasks. Let’s say you’re studying the 2014 Ebola epidemic. Perhaps your first task is to gather data to understand the nature and extent of the epidemic. Gathering good data isn’t easy but you don’t need any special skills beyond the ability to wrangle a spreadsheet or, at most, a relational database. Once you have the data, hopefully with a spatial dimension, you probably want to make a map or a set of maps. That’s the time to pull out a GIS program and figure out how to produce such a map. You don’t need to know everything about GIS, you just need to know how to make a map that will help you understand and communicate your research findings. Once you have a map maybe you’ll want to trace or attempt to model the “spatial diffusion” of the virus. To do so, conduct a literature search with keywords “ebola” and “spatial diffusion” or similar. Learn how others have done similar work. Don’t worry about reading Noel Cressie’s entire life work on spatial statistics, just figure out how to solve the problem you *need* to solve. You’ll be surprised at how much you learn along the way. You may also be surprised as you make faster progress than students around you who feel the need to reinvent every wheel before assembling a useful cart. Hope this helps you. Above all, be persistent in your quest. Buckle down and fight the good fight. Don’t run away.
Thank you very much for writing explicitly. I am grateful for your time and breaking down the problem. You understood perfectly my challenges.
Thank you for your Spatial Career Guide!
I am an undergraduate at UC Berkeley studying statistics. I took a GIS course last semester and I am very interested in combining my interests in statistics and GIS. It seems spatial statistician would be a great fit! I know I will go to graduate school sometime, but right now, I am more inclined to work for a few years first. I would appreciate if you could give me some guidance on what to do after graduation with only an undergrad statistics degree. Is it even recommended to work first?
Thank you in advance,
I’m so glad to hear some of this has been helpful to you. I think you have many good options. Working for a few years before grad school would be great as long as you can get a job where you’ll be learning applied methods and working with a dynamic team. If you can’t find that sort of situation then grad school would be a great option too. You may have an easier time finding a job with a Masters degree but the current job market for your skills is very hot. My advice is to look for a position where you’ll gain the most knowledge, rather than looking for the biggest paycheck. Good luck!
Thank you very much for your advice!