FutureMakers Mega Meetup on Wednesday, September 26, 2018

I will attend the FutureMakers Mega Meetup on Wednesday, September 26, 2018.  It will be hosted by RBC’s Tech Community Team.  The registration is free but required.  Here are the details.

Wednesday, September 26, 2018

4:30 PM – 8:00 PM

Metro Toronto Convention Centre, South Building

222 Bremner Boulevard

Toronto, ON

M5V 3L9

If you will attend this event, then please come and say “Hello”!

RBC FutureMakers Talks – “Management Lessons from Leading Tech Teams” – Tuesday, September 18, 2018

I will attend the RBC FutureMakers Talks on Tuesday, September 18.  The title of this event is “Management Lessons from Leading Tech Teams”.  Here are the details.

Tuesday, September 18, 2018

5:30 PM – 8:30 PM EDT

RBC WaterPark Place – Auditorium

88 Queens Quay West

Toronto, ON

M5J 0B8

 

If you will attend this event, please come and say “Hello”!

SORA Business Analytics Seminar – The role of geography in data integration and predictive analytics by Tony Lea – Friday, September 14, 2018

I will attend an upcoming seminar by Tony Lea, the Chief Methodologist at Environics Analytics.  The title of his seminar is “The role of geography in data integration and predictive analytics“.  Registration is free but required.

This seminar is organized by the Southern Ontario Regional Association (SORA) of the Statistical Society of Canada (SSC).  Here are the time, date, and location.

Friday, September 14, 2018

8:30 AM – 10:00 AM

Auditorium

RBC WaterPark Place

88 Queens Quay West

Toronto, ON

M5J 0B8

 

RBC WaterPark Place is conveniently located in downtown Toronto, and it is easily accessible from Union subway station.

If you will attend this seminar, then please feel free to come and say “Hello”!

Full disclosure: I work as a Digital Marketing Analyst at Environics Analytics.  Tony is my co-worker.

 

My Alumni Profile by Simon Fraser University – Where Are They Now?

I am happy and grateful to be featured by my alma mater, Simon Fraser University (SFU), in a recent profile.  I answered questions about how my transition from my academic education to my career in statistics and about how blogging and social media have helped me to advance my career.  Check it out!

During my undergraduate degree at SFU, I volunteered at its Career Services Centre for 5 years as a career advisor in its Peer Education program.  I began writing for its official blog, the Career Services Informer (CSI), during that time.  I have continued to write career advice for the CSI as an alumnus, and it is always a pleasure to give back to this wonderful centre!

You can find all of my advice columns here on my blog.

New Job at the Bank of Montreal in Toronto

I have accepted an offer from the Bank of Montreal to become a Manager of Operational Risk Analytics and Modelling at its corporate headquarter office in Toronto.  Thus, I have resigned from my job at the British Columbia Cancer Agency.  I will leave Vancouver at the end of December, 2015, and start my new job at the beginning of January, 2016.

I have learned some valuable skills and met some great people here in Vancouver over the past 2 years.  My R programming skills have improved a lot, especially in text processing.  My SAS programming skills have improved a lot, and I began a new section on my blog to SAS programming as a result of what I learned.  I volunteered and delivered presentations for the Vancouver SAS User Group (VanSUG) – once on statistical genetics, and another on sampling strategies in analytical chemistry, ANOVA, and PROC TRANSPOSE.  I have thoroughly enjoyed meeting some smart and helpful people at the Data Science, Machine Learning, and R Programming Meetups.

I lived in Toronto from 2011 to 2013 while pursuing my Master’s degree in statistics at the  University of Toronto and working as a statistician at Predicum.  I look forward to re-connecting with my colleagues there.

Eric’s Enlightenment for Thursday, June 4, 2015

1. IBM explains how Watson the computer answered the Final Jeopardy question against Ken Jennings and Brad Rutter.  (In a question about American airports, Watson’s answer was “What is Toronto???”  It’s not as ridiculous as you think, and Watson didn’t wager a lot of money for this answer – so it still won by a wide margin.)
2. Two views on how to reform FIFA by Nate Silver and Branko Milanovic – this is an interesting opportunity to apply good principles of institutional design and political economy.
3. How blind people navigate the Internet.
4. The Replication Network – a web site devoted to the study of replications in economics.
5. Cryptochromes and particularly the molecule flavin adenine dinucleotide (FAD) that forms part of the cryptochrome, are thought to be responsible for magnetoreception, the ability of some animals to navigate in Earth’s magnetic field.  Joshua Beardmore et al. have developed a microscope that can detect the magnetic properties of FAD – some very cool work on radical pair chemistry!

How to Find a Job in Statistics – Advice for Students and Recent Graduates

Introduction

A graduate student in statistics recently asked me for advice on how to find a job in our industry.  I’m happy to share my advice about this, and I hope that my advice can help you to find a satisfying job and develop an enjoyable career.  My perspectives would be most useful to students and recent graduates because of my similar but unique background; I graduated only 1.5 years ago from my Master’s degree in statistics at the University of Toronto, and I volunteered as a career advisor at Simon Fraser University during my Bachelor’s degree.  My advice will reflect my experience in finding a job in Toronto, but you can probably find parallels in your own city.

Most of this post focuses on soft skills that are needed to find any job; I dive specifically into advice for statisticians in the last section.  Although the soft skills are general and not specific to statisticians, many employers, veteran statisticians, and professors have told me that students and recent graduates would benefit from the focus on soft skills.  Thus, I discuss them first and leave the statistics-specific advice till the end.

Presentation Slides – Finding Patterns in Data with K-Means Clustering in JMP and SAS

My slides on K-means clustering at the Toronto Area SAS Society (TASS) meeting on December 14, 2012, can be found here.

This image is slightly enhanced from an image created by Weston.pace from Wikimedia Commons.

My Presentation on K-Means Clustering

I was very pleasured to be invited for the second time by the Toronto Area SAS Society (TASS) to deliver a presentation on machine learning.  (I previously presented on partial least squares regression.)  At its recent meeting on December 14, 2012, I introduced an unsupervised learning technique called K-means clustering.

I first defined clustering as a set of techniques for identifying groups of objects by maximizing a similarity criterion or, equivalently, minimizing a dissimilarity criterion.  I then defined K-means clustering specifically as a clustering technique that uses Euclidean proximity to a group mean as its similarity criterion.  I illustrated how this technique works with a simple 2-dimensional example; you can follow along this example in the slides by watching the sequence of images of the clusters toward convergence.  As with many other machine learning techniques, some arbitrary decisions need to be made to initiate the algorithm for K-means clustering:

1. How many clusters should there be?
2. What is the mean of each cluster?

I provided some guidelines on how to make these decisions in these slides.