Connect with local employers

I keep telling stu­dents that there are lots of jobs in data sci­ence (includ­ing sta­tis­tics), and they often tell me they can’t find them adver­tised. As usual, you do have to do some net­work­ing, and one of the best ways of doing it is via a Data Sci­ence Meetup. Many cities now have them includ­ing Mel­bourne, Syd­ney, Lon­don, etc. It is the per­fect oppor­tu­nity to meet with local employ­ers, many of which are hir­ing due to the huge expan­sion in the use of data analy­sis in busi­ness (aka busi­ness analytics).

At the end of each Mel­bourne meetup, some employ­ers have been adver­tis­ing their cur­rent ana­lytic job open­ings to the audience.

Now the local orga­niz­ers are going to extend the oppor­tu­nity to allow job-​​searchers to give a 90 sec­ond pitch to employ­ers. Details are pro­vided on the mes­sage board.

Visit of Di Cook

Next week, Pro­fes­sor Di Cook from Iowa State Uni­ver­sity is vis­it­ing my research group at Monash Uni­ver­sity. Di is a world leader in data visu­al­iza­tion, and is espe­cially well-​​known for her work on inter­ac­tive graph­ics and the XGobi and GGobi soft­ware. See her book with Deb Swayne for details.

For those want­ing to hear her speak, read on. Con­tinue reading →

European talks. June-​​July 2014

For the next month I am trav­el­ling in Europe and will be giv­ing the fol­low­ing talks.

17 June. Chal­lenges in fore­cast­ing peak elec­tric­ity demand. Energy Forum, Sierre, Valais/​Wallis, Switzerland.

20 June. Com­mon func­tional prin­ci­pal com­po­nent mod­els for mor­tal­ity fore­cast­ing. Inter­na­tional Work­shop on Func­tional and Oper­a­to­r­ial Sta­tis­tics. Stresa, Italy.

24–25 June. Func­tional time series with appli­ca­tions in demog­ra­phy. Hum­boldt Uni­ver­sity, Berlin.

1 July. Fast com­pu­ta­tion of rec­on­ciled fore­casts in hier­ar­chi­cal and grouped time series. Inter­na­tional Sym­po­sium on Fore­cast­ing, Rot­ter­dam, Netherlands.

Creating a handout from beamer slides

I’m about to head off on a speak­ing tour to Europe (more on that in another post) and one of my hosts has asked for my pow­er­point slides so they can print them. They have made two false assump­tions: (1) that I use pow­er­point; (2) that my slides are sta­tic so they can be printed.

Instead, I pro­duced a cut-​​down ver­sion of my beamer slides, leav­ing out some of the ani­ma­tions and other fea­tures that will not print eas­ily. Then I pro­duced a pdf file with sev­eral slides per page. Con­tinue reading →

Automatic time series forecasting in Granada

In two weeks I am pre­sent­ing a work­shop at the Uni­ver­sity of Granada (Spain) on Auto­matic Time Series Fore­cast­ing.

Unlike most of my talks, this is not intended to be pri­mar­ily about my own research. Rather it is to pro­vide a state-​​of-​​the-​​art overview of the topic (at a level suit­able for Mas­ters stu­dents in Com­puter Sci­ence). I thought I’d pro­vide some his­tor­i­cal per­spec­tive on the devel­op­ment of auto­matic time series fore­cast­ing, plus give some com­ments on the cur­rent best prac­tices. Con­tinue reading →

Online course on forecasting using R

I am team­ing up with Rev­o­lu­tion Ana­lyt­ics to teach an online course on fore­cast­ing with R. Top­ics to be cov­ered include sea­son­al­ity and trends, expo­nen­tial smooth­ing, ARIMA mod­el­ling, dynamic regres­sion and state space mod­els, as well as fore­cast accu­racy meth­ods and fore­cast eval­u­a­tion tech­niques such as cross-​​validation. I will talk about some of my con­sult­ing expe­ri­ences, and explain the tools in the fore­cast pack­age for R.

The course will run from 21 Octo­ber to 4 Decem­ber, for two hours each week. Par­tic­i­pants can net­work and inter­act with other prac­ti­tion­ers through an online com­mu­nity. Con­tinue reading →

Man vs Wild Data

I’m speak­ing on this topic at the Young Sta­tis­ti­cians Con­fer­ence, 7–8 Feb­ru­ary 2013.

If you’re a young sta­tis­ti­cian and live in Aus­tralia, please book in. It promises to be a great cou­ple of days. Early reg­is­tra­tions close on 2 January.

Abstract for my talk:

For 25 years I have been an intre­pid sta­tis­ti­cal con­sul­tant, tack­ling the wild fron­tiers of real data, real prob­lems and real time con­straints. I have faced prob­lems rang­ing from lin­guis­tics to river beds, from mak­ing paper plates to sell­ing pies at the MCG, from tax office audits to sur­veys about the colour pur­ple. Uni­ver­sity edu­ca­tion helps pre­pare you to be a sta­tis­ti­cal con­sul­tant in the same way that Google maps helps pre­pare you to cross the Simp­son Desert. You have some idea of the main fea­tures, but when you get there, noth­ing looks familiar.

I will describe some of my adven­tures, and explain how to bluff your way through igno­rance, work with inad­e­quate tools, and deal with smelly clients. I will tell you the story of the client who wouldn’t give me the data, the client who wouldn’t tell me the prob­lem, and the client who wanted all meet­ings held at ran­dom loca­tions for secu­rity reasons.

Along the way we will learn about the skills that sta­tis­ti­cians need to sur­vive in the wild.