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<h1><a href="https://seanjtaylor.com/">Sean J. Taylor</a></h1>
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<h1 id="hi">Hi!</h1>
<p>I am a <a href="#data-science">data scientist</a>, <a href="#social-science">social scientist</a>, <a href="#statistics">statistician</a>, and <a href="#software">software developer</a>. I mostly specialize in methods for solving causal inference and business decision problems, and I am particularly interested in building tools for practitioners working on real-world problems. I’m a generalist, I like to hang out with people from many fields and borrow as many ideas as possible. I have collaborated with computer scientists, economists, political scientists, statisticians, machine learning researchers, and business school scholars. It’s fun for me to jump around a bit, continue learning new things, and make connections between fields.</p>
<p>Here are some useful links:</p>
<ul>
<li><a href="https://www.motifanalytics.com">Motif Analytics</a> (my startup)</li>
<li><a href="https://twitter.com/seanjtaylor">Twitter</a></li>
<li><a href="https://notes.causal.engineering">Sign up for my newsletter</a></li>
<li><a href="https://github.com/seanjtaylor">Github</a></li>
<li><a href="https://www.linkedin.com/in/seanjtaylor/">LinkedIn</a></li>
<li><a href="https://scholar.google.com/citations?hl=en&authuser=1&user=2VHQIgQAAAAJ">Google Scholar</a></li>
<li><a href="blog/">My infrequently updated blog</a></li>
</ul>
<h2 id="background">Background</h2>
<ul>
<li>[2022-Present] I’m a co-founder and chief scientist at <a href="https://www.motifanalytics.com">Motif Analytics</a> <a href="https://motifanalytics.medium.com/bringing-more-causality-to-analytics-d378108bb15">Read more here!</a></li>
<li><a href="https://www.linkedin.com/in/seanjtaylor/">2019-2022</a> I was a data scientist and manager on the Rideshare Labs team at <a href="https://www.lyft.com/">Lyft</a>.</li>
<li>2012-2019, I was a research scientist and manager on Facebook’s <a href="https://research.fb.com/teams/core-data-science/">Core Data Science Team</a>.</li>
<li>2008-2013, I was a Ph.D. student at NYU’s Stern School of Business, concentrating in <a href="https://en.wikipedia.org/wiki/Information_system#The_academic_discipline">Information Systems</a>. My dissertation was titled <a href="https://www.dropbox.com/s/hsqc2pqs2rhqz9x/published_version.pdf">Social Influence from Online Social Signals</a>. My advisor was <a href="http://web.mit.edu/sinana/www/">Sinan Aral</a>.</li>
<li>2006-2008, I was a software engineer at <a href="https://www.matrixgroup.net/">Matrix Group, International</a>.</li>
<li>2004-2006, I was a research assistant at the <a href="https://www.federalreserve.gov/">Federal Reserve Board</a>.</li>
<li>2000-2004, I was an undergraduate at The University of Pennsylvania. I studied Economics, Finance, and Information Systems.</li>
<li>I grew up in Philadelphia and I’m a <a href="https://www.youtube.com/watch?v=qW1xbhW2PEE">huge Eagles fan</a>.</li>
</ul>
<h2 id="videos-and-podcasts">Videos and Podcasts</h2>
<ul>
<li><a href="https://open.spotify.com/episode/4Bt2oPRI2PlhPXUtHmKMja?si=Nribl563SOmOmbN3tducDA">What’s New in Data?</a> podcast with <a href="https://www.linkedin.com/in/johnkutay/">John Kutay</a>.</li>
<li><a href="https://www.youtube.com/watch?v=t6m9z874SLM&t=2s">When not to use SQL</a> a talk at <a href="https://normconf.com">NormConf</a>.</li>
<li><a href="https://open.spotify.com/episode/1PO8uLXraYFmEJUGs3mYDW?si=FIBcMvu_RuisrQjkeRmRTQ">Minimum Viable Experimentation</a> on the <a href="https://roundup.getdbt.com/s/the-analytics-engineering-podcast">Analytics Engineering Podcast</a></li>
<li><a href="https://www.youtube.com/watch?v=1W3PIwhfMsg&feature=youtu.be">Causal Inference and Sequence Data</a> on the <a href="https://www.superdatascience.com/podcast">Super Data Science podcast</a>.</li>
<li><a href="https://www.youtube.com/watch?v=5Myw5A-ZILs">The Relationship between Experimentation and Causal Inference</a> talk at the Nubank Data Science meetup.</li>
<li><a href="https://www.youtube.com/watch?v=0udCtHT0kGk">Causal Inference Approach to Matching in Two-Sided Marketplaces</a>.</li>
<li><a href="https://thedataexchange.media/the-evolution-of-the-data-science-role-and-of-data-science-tools/">Interview on The Data Exchange Podcast</a> with <a href="https://twitter.com/bigdata">Ben Lorica</a> and <a href="https://www.linkedin.com/in/jennwebb/">Jenn Webb</a>.</li>
<li><a href="https://youtu.be/2dv7NrYExzo?t=572">When do we actually need Causal Inference</a> talk at the <a href="https://nyhackr.org/">New York Open Statistical Programming Meetup</a>.</li>
<li><a href="https://twimlai.com/causal-models-in-practice-at-lyft-with-sean-taylor/">TWIML Interview on Causal Models in Practice</a> with <a href="https://twitter.com/samcharrington">Sam Charrington</a>.</li>
<li><a href="https://www.youtube.com/watch?v=ceCQh73dU98">Interview on the Gradient Dissent Podcast</a> with <a href="https://www.linkedin.com/in/lbiewald/">Lukas Biewald</a>.</li>
<li><a href="https://www.learnbayesstats.com/episode/37-prophet-time-series-causal-inference-sean-taylor">Learning Bayesian Statistics Podcast</a> episode with <a href="https://twitter.com/alex_andorra">Alex Andorra</a>.</li>
<li><a href="https://www.youtube.com/watch?v=oTeygIetj34">My Keynote</a> entitled “In Defense of Curve Fitting” at the <a href="https://causalscience.org/">2020 Causal Data Science Meeting</a></li>
<li><a href="https://www.youtube.com/watch?v=pOYAXv15r3A">A short talk about Prophet</a></li>
<li><a href="https://www.youtube.com/watch?v=OaTAe4W9IfA">Another talk about Prophet</a> at StanCon, with my friend <a href="http://lethalletham.com/">Ben Letham</a>.</li>
<li><a href="https://casualinfer.libsyn.com/causal-inference-for-data-science-with-sean-taylor">Interview on the Casual Inference Podcast</a></li>
<li><a href="https://nssdeviations.com/episode-35-special-guest-sean-taylor">Appearance on Not So Standard Deviations</a> with my friends <a href="https://hilaryparker.com/about-hilary-parker/">Hilary Parker</a> and <a href="http://www.biostat.jhsph.edu/~rpeng/">Roger Peng</a>.</li>
<li><a href="https://www.youtube.com/watch?v=ahaxt6UKxQw">A short interview about exploratory data analysis</a></li>
<li><a href="https://soundcloud.com/oreilly-radar/ratings-rankings-and-the">Podcast about my Science paper</a> with my friends <a href="http://www.johnmyleswhite.com/">John Myles White</a> and <a href="https://hilarymason.com/">Hilary Mason</a>.</li>
<li><a href="https://www.youtube.com/watch?v=EcB1dqQ1pyU&t=1s">Finding Nate Silver</a>, an <a href="http://www.ignitetalks.io/">Ignite talk</a> about a prediction market I co-developed.</li>
</ul>
<h2 id="--data-science"><a name="data-science"> </a> Data Science</h2>
<p>Here are some data science posts I’ve written:</p>
<ul>
<li><a href="https://medium.com/@seanjtaylor/a-personal-retrospective-on-prophet-f223c2378985">A Personal Retrospective on Prophet</a></li>
<li><a href="https://motifanalytics.medium.com/bringing-more-causality-to-analytics-d378108bb15">Bringing more causality to data science</a></li>
<li><a href="https://notes.causal.engineering/archive/locally-optimal/">Locally Optimal</a></li>
<li><a href="https://medium.com/@seanjtaylor/designing-and-evaluating-metrics-5902ad6873bf">Designing and Evaluating Metrics</a></li>
<li><a href="https://medium.com/@seanjtaylor/the-personality-space-of-cartoon-characters-e1d7b2009c15">The Personality Space of Cartoon Characters</a></li>
<li><a href="https://www.facebook.com/notes/facebook-data-science/nfl-fans-on-facebook/10151298370823859/">NFL Fans on Facebook</a></li>
<li><a href="https://www.facebook.com/notes/mike-develin/debunking-princeton/10151947421191849/">Debunking Princeton</a></li>
<li><a href="/post/39573264781/the-statistics-software-signal.html">The Statistics Software Signal</a></li>
<li><a href="https://seanjtaylor.com/2013/01/26/real-scientists-make-their-own-data.html">Real scientists make their own data</a></li>
</ul>
<h2 id="--social-science"><a name="social-science"> </a> Social Science</h2>
<p>Here are some of my social science papers. Almost all papers are field experiments on online social platforms.</p>
<ul>
<li><a href="https://link.springer.com/article/10.1007/s11129-020-09224-9">Displaying things in common to encourage friendship formation: A large randomized field experiment</a> (Quantitative Marketing and Economics) <a href="https://arxiv.org/abs/1905.02762">(pdf of conference version)</a></li>
<li><a href="https://dl.acm.org/doi/abs/10.1145/3274467">Characterizing online public discussions through patterns of participant interactions</a> (CSCW 2018)</li>
<li><a href="https://science.sciencemag.org/content/341/6146/647.abstract">Social Influence Bias: A Randomized Experiment</a> (Science)</li>
<li><a href="https://dl.acm.org/doi/abs/10.1145/3038912.3052666">Discussion quality diffuses in the digital public square</a> (WWW 2017)</li>
<li><a href="https://arxiv.org/abs/1311.2878">Selection Effects in Online Sharing: Consequences for Peer Adoption</a> (EC 2013)</li>
</ul>
<h2 id="--experimentation-and-statistics"><a name="statistics"> </a> Experimentation and Statistics</h2>
<p>Here are some of my papers on experimentation and statistics. I’m relatively new to this field and mostly a consumer of statistics research, rather than a producer.</p>
<ul>
<li><a href="https://dl.acm.org/doi/10.1145/3391403.3399542">Variance-Weighted Estimators to Improve Sensitivity in Online Experiments</a> (EC 2020) <a href="https://www.dropbox.com/s/dcft3h0pw304gbx/EC_2020.pdf?dl=0">(pdf)</a>. You can watch <a href="https://www.youtube.com/watch?v=kgIwougeN0M">a presentation</a> by my co-author <a href="https://www.linkedin.com/in/kevinycliou/">Kevin Liou</a>.</li>
<li><a href="https://arxiv.org/pdf/1709.09636.pdf">Randomized experiments to detect and estimate social influence in networks</a> (Complex Spreading Phenomena in Social Systems). This is a book chapter with my friend <a href="https://www.deaneckles.com/">Dean Eckles</a>.</li>
<li><a href="https://projecteuclid.org/euclid.aoas/1600454862">Active Matrix Factorization for Surveys</a> (Annals of Applied Statistics)</li>
<li><a href="https://www.tandfonline.com/doi/abs/10.1080/00031305.2017.1380080?journalCode=utas20&">Forecasting at Scale</a> (The American Statistician) <a href="http://lethalletham.com/ForecastingAtScale.pdf">(pdf)</a></li>
</ul>
<h2 id="--forecasting-software"><a name="software"> </a><a></a> Forecasting Software</h2>
<ul>
<li><a href="https://facebook.github.io/prophet/">Prophet</a> is an open source forecasting package available in R and Python. You can watch <a href="https://www.youtube.com/watch?v=pOYAXv15r3A">my talk about Prophet</a>. You can also read my <a href="https://twitter.com/seanjtaylor/status/1123278380369973248">explainer thread</a>.</li>
</ul>
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