New Job as Data Science Consultant at Environics Analytics!

I am very excited to start a new job as a Data Science Consultant at Environics Analytics (EA)!  My new position is a dual role of data scientist and consultant – I will meet clients regularly to advise them on statistical modelling, data analysis, and marketing analytics, and I will conduct statistical research on a variety of problems.  I look forward to learning about and working in EA’s specialty of geodemography, as well as researching new areas of data analytics, such as text mining and sentiment analysis.

I began my new job in mid-August, and I have enjoyed meeting my new co-workers and serving my first client so far.  I have opened a second Twitter feed, @EricCaiEA, to share my work at my new company.  You can continue to find me on my own Twitter feed for The Chemical Statistician, @chemstateric.

eric-cai-in-front-of-ea-logo

Data Science Seminar by David Campbell on Approximate Bayesian Computation and the Earthworm Invasion in Canada

My colleague, David Campbell, will be the feature speaker at the next Vancouver Data Science Meetup on Thursday, June 25.  (This is a jointly organized event with the Vancouver Machine Learning Meetup and the Vancouver R Users Meetup.)  He will present his research on approximate Bayesian computation and Markov Chain Monte Carlo, and he will highlight how he has used these tools to study the invasion of European earthworms in Canada, especially their drastic effects on the boreal forests in Alberta.

Dave is a statistics professor at Simon Fraser University, and I have found him to be very smart and articulate in my communication with him.  This seminar promises to be both entertaining and educational.  If you will attend it, then I look forward to seeing you there!  Check out Dave on Twitter and LInkedIn.

Title: The great Canadian worm invasion (from an approximate Bayesian computation perspective)

Speaker: David Campbell

Date: Thursday, June 25

Place:

HootSuite (Headquarters)

5 East 8th Avenue

Vancouver, BC

Schedule:

• 6:00 pm: Doors are open – feel free to mingle!
• 6:30 pm: Presentation begins.
• ~7:45 Off to a nearby restaurant for food, drinks, and breakout discussions.

Abstract:

After being brought in by pioneers for agricultural reasons, European earthworms have been taking North America by storm and are starting to change the Alberta Boreal forests. This talk uses an invasive species model to introduce the basic ideas behind estimating the rate of new worm introductions and how quickly they spread with the goal of predicting the future extent of the great Canadian worm invasion. To take on the earthworm invaders, we turn to Approximate Bayesian Computation methods. Bayesian statistics are used to gather and update knowledge as new information becomes available owing to their success in prediction and estimating ongoing and evolving processes. Approximate Bayesian Computation is a step in the right direction when it’s just not possible to actually do the right thing- in this case using the exact invasive species model is infeasible. These tools will be used within a Markov Chain Monte Carlo framework.

About Dave Campbell:

Dave Campbell is an Associate Professor in the Department of Statistics and Actuarial Science at Simon Fraser University and Director of the Management and Systems Science Program. Dave’s main research area is at the intersections of statistics with computer science, applied math, and numerical analysis. Dave has published papers on Bayesian algorithms, adaptive time-frequency estimation, and dealing with lack of identifiability. His students have gone on to faculty positions and worked in industry at video game companies and predicting behaviour in malls, chat rooms, and online sales.

Vancouver Machine Learning and Data Science Meetup – NLP to Find User Archetypes for Search & Matching

I will attend the following seminar by Thomas Levi in the next R/Machine Learning/Data Science Meetup in Vancouver on Wednesday, June 25.  If you will also attend this event, please come up and say “Hello”!  I would be glad to meet you!

Eric Cai - Official Head Shot

To register, sign up for an account on Meetup, and RSVP in the R Users Group, the Machine Learning group or the Data Science group.

     Title: NLP to Find User Archetypes for Search & Matching

     Speaker: Thomas Levi, Plenty of Fish

     Location: HootSuite, 5 East 8th Avenue, Vancouver, BC

     Time and Date: 6-8 pm, Wednesday, June 25, 2014

 

Abstract

As the world’s largest free dating site, Plenty Of Fish would like to be able to match with and allow users to search for people with similar interests. However, we allow our users to enter their interests as free text on their profiles. This presents a difficult problem in clustering, search and machine learning if we want to move beyond simple ‘exact match’ solutions to a deeper archetypal user profiling and thematic search system. Some of the common issues that arise are misspellings, synonyms (e.g. biking, cycling and bicycling) and similar interests (e.g. snowboarding and skiing) on a several million user scale. In this talk I will demonstrate how we built a system utilizing topic modelling with Latent Dirichlet Allocation (LDA) on a several hundred thousand word vocabulary over ten million+ North American users and explore its applications at POF.

 

Bio

Thomas Levi started out with a doctorate in Theoretical Physics and String Theory from the University of Pennsylvania in 2006. His post-doctoral studies in cosmology and string theory, where he wrote 19 papers garnering 650+ citations, then took him to NYU and finally UBC.  In 2012, he decided to move into industry, and took on the role of Senior Data Scientist at POF. Thomas has been involved in diverse projects such as behaviour analysis, social network analysis, scam detection, Bot detection, matching algorithms, topic modelling and semantic analysis.

 

Schedule
• 6:00PM Doors are open, feel free to mingle
• 6:30 Presentations start
• 8:00 Off to a nearby watering hole (Mr. Brownstone?) for a pint, food, and/or breakout discussions

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.

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