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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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