artificial intelligence

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 <article>
 	<h1>Data Scientist</h1>
 	<section>
 		<address class="h-card">
 			by
 			<a rel="author" class="u-url" href="http://changelog.ca/"><span class="p-given-name">Charles</span> <span class="p-additional-name">Iliya</span> <span class="p-family-name">Krempeaux</span></a>
 		</address>
 	</section>
 	<section>
 		<p>
 			A <strong>data scientist</strong> is someone who does <ziba-link>data science</ziba-link>.
 			And typically doing it while working at a company.
 		</p>
 	</section>
 	<section>
 		<h2>Data Scientist Role and Title</h2>
 		<p>
 			The title of "<strong>data scientist</strong>" does not exist in-a-vacuum — does <em>not</em> stand alone, cut off from other influences, without links to the outside world.
 			"<strong>Data Scientist</strong>" is a title associated with a type of role (or roles) that companies hire for.
 		</p>
 		<p>
 			Who is a <strong>data scientist</strong>‽
 			Although an unsatisfying answer to some — in practice a <strong>data scientist</strong> is anyone a company gives the title of "<strong>data scientist</strong>" to.
 		</p>
 		<p>
 			What types of skills and specializations are more likely to get someone hired as a <strong>data scientist</strong>‽
 			It depends on the company, but —
 		</p>
 		<p>
 			When working at a company, many <strong>data scientists</strong>' —
 		</p>
 		<ul>
 			<li>do <ziba-link transform="lowercase">A-B testing</ziba-link>,</li>
 			<li>do <ziba-link>fraud detection</ziba-link>,</li>
 			<li>work on <ziba-link>online advertising</ziba-link>, or</li>
 			<li>create <ziba-link>visualization</ziba-link>s for others at the company they are working at.</li>
 		</ul>
 		<p>
 			Not all <strong>data scientists</strong> do this type of work — but many do.
 		</p>
 	</section>
 	<section>
 		<h2>Data Analysts</h2>
 		<p>
 			In practice, the name "<strong>data scientist</strong>" at many companies was just a new name for "<ziba-link>data analyst</ziba-link>".
 			Many <strong>data analysts</strong> became <strong>data scientist</strong> after the title of <strong>data scientist</strong> became popular — continuing to do the exact same job at the exact same company just with a new newly popular title.
 		</p>
 		<p>
 			This type of changing of titles is common in the tech-industry.
 			It is similar to the how <strong>system administrators</strong> (<abbr title="system administrators">sysadmins</abbr>) became <strong>operations</strong> (<strong><abbr title="operations">ops</abbr></strong>) specialists, and then became <strong>DevOps</strong> people, and then became <strong>site reliability engineers</strong> (<strong><abbr title="site reliability engineer">SRE</abbr></strong>).
 		</p>
 		<p>
 			At many companies the same people doing the same work for the same job simply had their title changed to whatever became popular at the time.
 		</p>
 	</section>
 	<section>
 		<h2>Software Developers</h2>
 		<p>
 			Although <strong>"data science"</strong> and the title of <strong>"data scientist"</strong> hadn't been coined yet — in the 2000s, it was more common for some of the more technical things that <strong>data scientists</strong> do to just be part of <strong>software development</strong>.
 			Especially for the things that would have been called "<strong>artificial intelligence</strong>" at the time.
 		</p>
 		<p>
 			However, this started to change around 2012.
 			Some of types of activities started to be done by people with <em>little</em> to <em>no</em> (often <em>no</em>) <strong>software development</strong> background.
 		</p>
 		<p>
 			From a <strong>software developer</strong> point-of-view, most <strong>data scientists</strong> are '<strong>users</strong>'.
 			The vast majority of <strong>data scientists</strong> will <em>never</em>, for example, implement an <ziba-link>artificial neural network</ziba-link>, or implement a <ziba-link>training</ziba-link> algorithm, or implement a visualization rendering algorithm, etc.
 			And the vast majority of <strong>data scientists</strong> will <em>never</em> do these things because they do <em>not</em> have the skills to do it.
 			The vast majority of <strong>data scientists</strong> use tools created by <strong>software developers</strong>.
 		</p>
 		<p>
 			Most <strong>data scientists</strong> cannot program.
 			But some can.
 		</p>
 		<p>
 			But the minority of <strong>data scientists</strong> who can program, the vast majority of <strong>data scientists</strong> who can program do <em>not</em> program like a <strong>software developer</strong>.
 			These <strong>data scientists</strong> use programming languages (such as the <ziba-link>r programming language</ziba-link> or the <ziba-link>python programming language</ziba-link>) in a way that a <strong>software developer</strong> would use <ziba-link>bash</ziba-link> from a <ziba-link>computer-terminal</ziba-link>.
 			I.e., most of the <strong>data scientists</strong> who can program use programming languages to just issue commands.
 		</p>
 		<p>
 			For an analogy that may help make this clearer —
 			When a <strong>software developer</strong> writes a program, they are (metaphorically speaking) creating a <em>robot</em> that is expecting to run independently 24 hours a day, 7 days a week, and be able to function independently in the world.
 			However, when a <strong>data scientist</strong> writes a program, it is a (from a <strong>software developer</strong>'s point-of-view) a very very 'hacky' tool that the <strong>data scientist</strong> would have to manually use themselves — and perhaps modify each time they use it.
 		</p>
 	</section>
 	<section>
 		<h2>Physicists<h2>
 		<p>
 			There has been a type of scam that has been going on in universities with the study of <strong>physics</strong>.
 		</p>
 		<p>
 			Many (probably most) people who <em>go to</em> and <em>pay money for</em> university do so for career and work related reasons.
 			They either want to get a higher paying job, after they graduate from university, than they would have been able to get without having gone to university.
 			Or they want to avoid doing physical labor, and want to be able to do a different type of job (that doesn't involve physical labor).
 			And they expect to do it doing whatever they studied.
 		</p>
 		<p>
 			The vast majority of people who study <strong>physics</strong> at university will never get a job as a <strong>physicist</strong>.
 			Never.
 			And the people working at the universities know this!
 		</p>
 		<p>
 			The people working at the universities know there are zero job prospects for the vast majority of these <strong>physicists</strong> they are graduating.
 			But not only do the people working at the universities not warn these students about this — but they happily take their money while they effectively letting them (and even encouraging them to) waste 4 to 10+ years of their lives getting BSc, MSc, and PhD in <strong>physics</strong>.
 		</p>
 		<p>
 			What happens to these <strong>physicists</strong>‽
 			In the past, some became <em>software developers</em>.
 			But since the title of <strong>data scientist<strong> got coined, many of them have become <strong>data scientists</strong>.
 		</p>
 		<p>
 			In fact, so many <strong>physicists</strong> have become <strong>data scientists</strong> that they caused a culture change.
 			Some ways <strong>data science</strong> culture seemed t haveo changed as a result of all these <strong>physicists</strong> flooding <strong>data science</strong> is:
 		</p>
 		<ul>
 			<li>
 				the <strong>physicists</strong> who flooded <strong>data science</strong> brought <strong>credentialism</strong> to the hiring of <strong>data scientists</strong>, even making it the norm, where before it wasn't common and previously there was more focus on whether a candidate <strong>data scientist<strong> did or did not have the skills the company was looking for,
 			</li>
 			<li>
 				the <strong>physicists</strong> who flooded <strong>data science</strong> made it so that the skills associated with installing and operating a <strong>database</strong> became uncommon among <strong>data scientists</strong>, where before that wasn't the case — this resulted in the creation of a new role to compensate for this — the <ziba-link>data engineer</ziba-link>,
 			</li>
 			<li>
 				the <strong>physicists</strong> who flooded <strong>data science</strong> made it so that software development skills became uncommon.
 			</li>
 		</ul>
 	</section>
 	<section>
 		<h2>Universities</h2>
 		<p>
 			Once the title of <strong>data scientist</strong> became popular, many universities rushed to exploit this for financial gain.
 		</p>
 		<p>
 			Many universities quickly created <strong>data science</strong> programs.
 			Many of these university <strong>data science</strong> programs were created by people who never actually worked at a <strong>data scientist</strong>.
 			And thus it was difficult for them to know what skills companies, who wanted to hire a <strong>data scientist</strong>, actually wanted <strong>data scientists</strong> they hired to have.
 		</p>
 	</section>
 </article>