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b'This week on Papa PhD, I\'m talking with Caolan Kovach-Orr about his journey from the wet lab to a career in data science. During our conversation, we talked Caolan\'s academic journey, about what skills you should focus on as a candidate, today, if you\'re interested in data science, about the specifics of the interviewing process for data scientist positions, and Caolan shared specific advice based on his experience as a PhD in the corporate space, so be ready to take notes!\\t\\t
\\n\\t\\t\\tWhat you\\u2019ll learn about in this episode:\\t\\t
\\n\\t\\tWhy you shouldn\'t compare yourself to others as an atypical candidateWhat companies are looking for in a candidate, when hiring a PhDWhy you should invest in learning PythonHow a public track record of writing code can help you stand out in the hiring processThe importance of letting go of ego when transitioning to a new domainWhen to start networking with potential employersWhat an 11-stage interview process look likeSalary negotiation best practicesDo you enjoy Papa PhD? Leave me a comment here\\xa0- one short sentence is enough! And be sure to include your Twitter handle \\u2013 that way, I can thank you personally!\\t\\t
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\\n\\t\\t\\t\\t\\t\\tSupport the show on Patreon !
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\\n\\t\\tCaolan Kovach-Orr Caolan earned his PhD in theoretical biology from McGill in 2015, his thesis focused on predator-prey interactions. He started, in industry, as a Data Scientist, and currently heads a data science & engineering team for Verisk Analytics. Caolan and his team continue to work on solving novel problems, such as getting regulatory approval for the US\'s first machine learning based insurance pricing product.\\t\\t
\\n\\t\\t\\tThank you, Caolan\\t\\t
\\n\\t\\tIf you enjoyed this interview with Caolan, let her know by clicking the link below and leaving him a message on Twitter:Click here to thank Caolan Kovach-Orr on LinkedIn!Click here to share your key take-away from this interview with David!\\t\\t
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\\n\\t\\t\\t\\t\\t\\tDownload "Tools for Your PhD Journey" !
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\\n\\t\\t\\tCaolan\\u2019s pearls of wisdom:\\t\\t
\\n\\t\\t\\u201cData science problems now are actually not that hard to code. There have been a lot of people who\'ve done a lot of work on open-source packages and, you know, 10 years ago somebody who could create a neural net model probably had to write the code for the neural net. Now there\'s hundreds, if not thousands of packages out there. Everything\'s kind of pre-configured, so the actual running of a model isn\'t that difficult. It may be knowing which model to use, knowing how to design your experiments, how to design your tests, how to design your data that can really make the big difference between something that works really well and something that\'s okay. And that\'s where\\xa0you want to be as a PhD, as somebody who can do something really well. Because, honestly, I can teach most undergrads from a comp sci background how to run a neural net in an afternoon, maybe a week. So you don\'t want to be competing with them \\u2013 they can just do it okay at that point. You want to be the person who can bring that next level of value.\\u201d\\u201cMoving up the corporate ladder is not about who\'s the best. It\'s just not. It\'s about who can help the most people. So you don\'t get that manager, directorship or VP position because you\'re the smartest person in the room \\u2013 you get it because you will be able to help the people who report in to you and the people who you report to the most in that position, and so there\'s almost no room for ego.\\u201d\\t\\t
\\n\\t\\t\\tThis episode\\u2019s resources:\\t\\t
\\n\\t\\tCaolan Kovach-Orr | LinkedIn\\t\\t
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\\n\\t\\t\\t\\t\\t\\tJoin the Papa PhD Postgraduate Career Exploration Group!
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\\n\\t\\t\\tYou might also like the following episodes:\\t\\t
\\n\\t\\tGraydon Snider \\u2013 Building your path to data scienceSimon Moore \\u2013 Taking the leap into IndustryMargaret Magdesian \\u2013 From the bench to entrepreneurshipPaulo Oliveira \\u2013 Entrepreneurship and outreach as an academic\\t\\t
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