Tips for Building a Data Science Capability
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Alex Cosmas<br />
CHIEF DATA SCIENTIST<br />
@alexcosmas<br />
Brian Keller, PhD<br />
CHIEF TECHNOLOGIST<br />
@brndnlkllr<br />
Jamie Lopez, PhD<br />
SENIOR ASSOCIATE<br />
@jamielopezphd<br />
<strong>Data</strong> scientists should be<br />
truth-seekers, not fact-seekers.<br />
I’ll take passion over talent<br />
any day.<br />
Fundamentally, people drive the<br />
analysis and make the interpretations,<br />
so it follows the more talented<br />
your people then the better your<br />
analysis and interpretations.<br />
Patrick McCreesh<br />
Kristen More, PhD<br />
Ari Hamalian<br />
SENIOR ASSOCIATE<br />
@patrickmccreesh<br />
SENIOR ASSOCIATE<br />
@kristenmorephd<br />
LEAD ASSOCIATE<br />
@arihamalian<br />
Respect the data, bring on<br />
the science.<br />
All the data and tools in the world<br />
are meaningless unless you have<br />
the right data science talent to<br />
make sense of it.<br />
The cost of analysis will always be<br />
cheaper than the price of ignorance.<br />
Katie Hanley<br />
JD Hannick<br />
Susan Michener<br />
LEAD ASSOCIATE<br />
@katiekara<br />
LEAD ASSOCIATE<br />
@JDHannick<br />
LEAD ASSOCIATE<br />
@michenersusan<br />
42<br />
To make data science sing, hit the<br />
impact notes every day.<br />
<strong>Data</strong> doesn’t solve problems,<br />
people armed with data<br />
solve problems.<br />
Change agents are <strong>for</strong>ce multipliers –<br />
cultivating them to help drive your<br />
data science vision <strong>for</strong>ward is time<br />
well spent.
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