# Tag Archives: analytics

## We’re Hiring: Open-Rank, Tenure-Track

Open-Rank Tenure-Track Faculty Position in Management Science

The Management Science Department at the Miami Business School invites applications for an open-rank, tenure-track faculty position to begin in the fall of 2019. Applicants with research interests in all areas of Operations Research and Analytics will be considered.

Applicants should possess, or be close to completing, a Ph.D. in Operations Research, Operations Management, Industrial Engineering, or a related discipline by the start date of employment. The Management Science Department consists of a diverse group of faculty with expertise in Statistics and Operations Research. We seek candidates whose research and teaching interests complement and strengthen our existing departmental strengths. Responsibilities include research, which is expected to lead to top-tier publications, teaching at both the undergraduate and graduate levels, and service.

Applications should be submitted by e-mail to MASrecruiting@bus.miami.edu, and should include the following: a curriculum vitae, up to three representative publications, brief research and teaching statements, an official graduate transcript, information about teaching experience and evaluations (if available), and three letters of recommendation. All applications completed by December 1, 2018 will receive full consideration, but candidates are urged to submit all required material as soon as possible. Applications will be accepted until the position is filled. Candidates who are presenting at the INFORMS Annual Meeting in Phoenix are encouraged to include the details of their session in their cover letter. Our faculty attending the meeting will try to attend these presentations and may arrange for interviews whenever possible.

Salary is competitive and commensurate with qualifications and experience. This is a nine-month appointment and summer research support is anticipated from the Business School.

The University of Miami offers a comprehensive benefits package including medical and dental benefits, tuition remission, and much more. For additional information, visit https://www.hr.miami.edu/working-at-the-u/new-employee-total-rewards/index.html. The University is an equal opportunity employer and encourages candidates regardless of gender, race, color, ethnicity, age, disability status or sexual orientation to apply.

Filed under Analytics

## Tenure-Track Position in Big Data Analytics, University of Miami, School of Business

I’m very happy to announce that the School of Business at the University of Miami is hiring in my department! Details below. This is an exciting time to be involved in Business Analytics!

Tenure-Track Faculty Position in Management Science (Big Data Analytics)

The Management Science Department at the University of Miami’s School of Business Administration invites applications for a tenure-track faculty position at the junior or advanced Assistant Professor level to begin in the Fall of 2015. Exceptional candidates at higher ranks will be considered subject to additional approval from the administration. Salaries are extremely competitive and commensurate with background and experience. This is a nine-month appointment but generous summer research support is anticipated from the School of Business.

Applicants with research interests in all areas of Analytics will be considered, although primary consideration will be given to those with expertise in Big Data Analytics and the computational challenges of dealing with large data sets. Expertise in, or experience with, one or more of the following is particularly welcome: MapReduce/Hadoop, Mahout, Cassandra, cloud computing, mobile/wearable technologies, social media analytics, recommendation systems, data mining and machine learning, and text mining. The Management Science Department is a diverse group of faculty with expertise in several areas within Operations Research and Analytics, including statistics and machine learning, optimization, simulation, and quality management. Duties will include research and teaching at the graduate and undergraduate levels.

Applicants should possess, or be close to completing, a PhD in computer science, operations research, statistics, or a related discipline by the start date of employment. Applications should be submitted by e-mail to facultyaffairs@bus.miami.edu, and should include the following: a curriculum vitae, up to three representative publications, brief research and teaching statements, an official graduate transcript (for the junior Assistant Professor level), information about teaching experience and performance evaluations, and three letters of recommendation. All applications completed by December 1, 2014 will receive full consideration, but candidates are urged to submit all required material as soon as possible. Applications will be accepted until the position is filled.

The University of Miami offers a comprehensive benefits package including medical and dental benefits, tuition remission, vacation, paid holidays, and much more. The University of Miami is an Equal Opportunity/Affirmative Action Employer.

Filed under Analytics

## Should You Hire Security When Tenting Your House?

Last week I had my house tented because of termites. For those of you who don’t know what “tenting” is (I didn’t until about a year ago), it amounts to wrapping an entire house inside a huge tent and filling the tent with a poisonous gas that kills everything inside (and by everything I really do mean everything). Those who have been through this experience know what a hassle it is. We received a to-do list of pre-tenting tasks, which included:

• Remove or discard all food that isn’t canned or packaged in tightly-sealed, never-opened containers
• Turn off all A/C units and open one window in each room of the house
• Open all closet and cabinet doors
• Turn off all internal and external lights (including those operating on a timer)
• Prune/move all outdoor plants away from the house to have a clearance of at least 18 inches
• Soak the soil around the house (up to a foot away from the structure) on the day of the tenting
• Warn your neighbors about the tenting (so that they can keep their pets away from the house)
• etc.

We had to sleep two nights in a hotel, with two dogs, one of which had just had knee surgery. What an adventure!

The main point of concern was that the house would stay vulnerable (open windows) and unattended during the process. On top of that, one of our neighbors told us that he knew of a house that had been robbed during tenting a couple of months ago. So we started to consider hiring a security guard to sit outside the house for 48 hours. Would that be a good idea? Let’s think about this.

Our insurance’s deductible is $2500. I assume that if thieves are willing to risk their lives (wearing gas masks; oh yeah! they do that!) to enter a tented house, they’d steal more than$2500 worth of stuff. Therefore, being robbed would cost us $2500. This doesn’t take into account that one might have irreplaceable items in the house. However, most of the time those can be taken with you (unless they are too big or inconvenient to carry). In my case, I took the external hard drive to which I back up my data, and the mechanical pencil I’ve owned and used since 1991 (yes, you guessed right, the eraser at the end doesn’t exist any more). The security company we called would charge$15 per hour for an unarmed guard to be outside our house. Multiplying that by 48 hours brings the cost of hiring security to $720. Let’s say that the likelihood (a.k.a. probability) of being robbed while your house is tented without a security guard is $p_1$ (in percentage terms; for example, $p_1$ for the White House is pretty close to 0%), and when a security guard is on duty that likelihood is $p_2$. Unless $p_1 > p_2$, there’s no point in having this entire discussion, so I’ll assume that is true. Here’s a pretty neat rule of thumb that you can use: divide the cost of hiring security by your deductible to get a number $n$ between zero and one (of course, if hiring a guard costs more than your deductible, don’t do it!). Unless the presence of the guard reduces your chance of being robbed ($p_1$) by more than $n$, you should not hire security! (Later on, I’ll explain where this rule comes from.) For example, in my case 720/2500 is approximately equal to 29%. If the chance of being robbed without security is 30%, unless hiring a guard brings that chance down to 1% or less, it’s better not to do it. If the value of $p_1$ is less than or equal to 29% to begin with (I live in a reasonably safe neighborhood), the answer is also not to hire security (probabilities cannot be negative). This rule works regardless of the value of $p_1$; what matters is how great the improvement to $p_1$ is. In addition to looking at the numbers, we also took into account the following clause from the security company’s contract: …the Agency makes no warranty or guarantee, including any implied warranty of merchantability or fitness, that the service supplied will avert or prevent occurrences or the losses there from which the service is designed to detect or avert. In other words, if you hire us (the security company) and still get robbed, we have nothing to lose! So what did we do? We chose not to hire security and, fortunately, our house was not robbed. However, even though the tenting instructions say that you don’t have to wash your glasses and plates after returning home, we decided to do so anyway (as they say in Brazil: “seguro morreu de velho”). Disclaimer: The advice contained herein does not guarantee that your house will not be robbed. Use it at your own risk! Details of the Analysis So where does that rule of thumb come from? We can look at this problem from the point of view of a decision tree, as pictured below. In node 0, we make one of two decisions: hire a security guard (payoff = -$720, i.e. a cost), or not (payoff = -$0). For each of those decisions (branches), we create event nodes (1 and 2) to take into account the possibility of being robbed. At the top branch of the tree (node 2), the house will be robbed with probability $p_2$, in which case we incur an additional cost of$2500, and the house will be safe with probability $(1-p_2)$, in which case we incur no additional expense. Therefore, the expected monetary value of hiring security, which we call $EMV_2$, is to spend $720+$2500 with probability $p_2$, and to spend $720 with probability $(1-p_2)$. Hence $EMV_2 = - 3220p_2 - 720(1-p_2) = - 2500p_2 - 720$ Through a similar analysis of the bottom branch (node 1), we conclude that the expected monetary value of not hiring security, which we call $EMV_1$, is to spend$2500 with probability $p_1$ and to spend 0 with probability $(1-p_1)$. Therefore $EMV_1 = -2500p_1 - 0(1-p_1) = - 2500p_1$ Hiring security will be the best choice when it has greater expected monetary value than not hiring security, that is when $EMV_2 > EMV_1$, which yields $-2500p_2 - 720 > -2500p_1$ $\Downarrow$ $2500(p_1 - p_2) > 720$ $\Downarrow$ $p_1 - p_2 > \frac{720}{2500}$ which is the result we talked about earlier (recall that $p_1 > p_2$). How Does Analytics Fit In? The Analytics process is composed of three main phases: descriptive (what does the data tell you about what has happened?), predictive (what does the data tell you about what’s likely to happen?), and prescriptive (what should you do given what you learned from the data?). In this problem we can identify a descriptive phase in which we try to obtain probabilities $p_1$ and $p_2$. This could be accomplished by looking at police or insurance company records of robberies in your area. It’s not always possible to get a hold of those records, of course, so one might need to get a little creative in estimating those numbers. Having knowledge of the probabilities, the calculation described above could be classified as a prescriptive phase: what’s the course of action? Hire security if (cost of security)/(insurance deductible) < $p_1 - p_2$. There is no predictive phase here because our analysis does not require the knowledge of any future event (only how likely it is to occur). Operations Research can be used in some or all of these phases. Most of what I do in my research and consulting projects lies in the prescriptive phase (optimization). Recently, however, I’ve decided to broaden my horizons and learn more about the other two phases as well, starting with some self-teaching of data mining. 13 Comments ## INFORMS 2010 Wrap-Up I had a very productive and fun time at the INFORMS Annual Meeting in Austin, Texas. So I thought I’d share with you some of my observations about the meeting: • Analytics initiative by INFORMS: great idea! I believe that we (INFORMS members) have to jump onto the Analytics bandwagon and let everyone know that we can do Analytics too! It’s all about the power of words these days (see the country’s political arena for a perfect example). Starting today, I’ll tell everyone that I can do “Advanced Prescriptive Analytics” (optimization). • Panel on Social Networks: it was nice to hear from some of the most popular OR bloggers and learn about their motivations, fun stories, and blogging strategies. Great job Mike and Laura! • John Birge‘s plenary (Omega Rho Distinguished Lecture): very informative and entertaining. The simple and powerful take-home message was: align incentives. What’s good for the employees has to be good for the company as well. • RAS Problem Solving Competition: Michael Trick and I (a.k.a. Team MATHY) received an honorable mention at the Railway Applications Section (RAS) 2010 Challenge (certificate + photo :-). After watching the three finalists’ presentations, we were happy to see that our solution value of11,399,670.88 was equal to the best solution found by the winning team, and better than the solution found by the other two finalists. Nobody managed to prove optimality, though. Interestingly, none of the finalists thought about scaling the problem (thinking in terms of tanks of gasoline instead of gallons of gasoline), which made a huge difference in the performance of our model. Overall, it was a lot of fun to participate in this competition and I want to thank the organizers for putting it together. Here’s a picture of team MATHY with Juan Morales from BNSF Railway.

And here’s a picture of the railroad network we had to deal with:

• Technical sessions: I watched many interesting and inspiring talks (as a matter of fact, I had some great ideas for my own research while watching a number of presentations). It’s nice to see that *a lot* of people are using Latex Beamer these days. Let’s aim for a Powerpoint-free INFORMS by 2020!
• Idea for an iPhone App? I applaud the going-green initiative of reducing the number of conference program booklets that have to be printed out. However, for this to work it requires a lot of organization from each of us: we have to go over the program in advance, select the talks we want, and print the appropriate pages. I don’t know about you, but I never manage to get this done. So I propose we create an iPhone (mobile) app to allow participants to browse the program on-the-go. It’s not convenient to browse the program PDF on a phone. We need an app. We need to be able to filter by author, by chair, by topic/keyword, etc. We want a time-sensitive app that tells you what’s next. We want an app that sends notifications to your phone reminding you that a talk/event is coming up so that you ask for the check in time. If we had something like that, I think that a lot fewer people would ask for a printed program (myself included).
• Thumbs up for all the vegetarian food: being a vegetarian myself, I was impressed with the generous availability of vegetarian food (i.e. not only salad) at both the Sunday and Tuesday receptions. Well done!
• Austin’s Convention Center: in addition to being huge, the convention center’s numerous under-construction areas made it very hard to navigate from session to session. I always felt like I was taking the longest path from point A to point B.
• Meeting old and new friends: it was great to make many new friends and to meet old friends from my PhD days at Carnegie Mellon at the Tepper Alumni reception. I also had some very productive research meetings with several colleagues.

Last but not least, I’d like to thank John Hooker, Christopher Beck, and Willem-Jan van Hoeve for agreeing to give a talk in my session, and Willem for inviting me to present in his session.

Time to say bye-bye to weird Austin and fly back to Miami! Hence, I had to put on my “U” shirt: