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Using Data Science to Combat Youth Disparities - Data Science Pop-up Seattle

A machine-learning deep dive into the American Community Survey. Presented by Sean Green, Research Data Analyst at <br>City of Seattle. For more information on machine learning click on our website.

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Using Data Science to Combat Youth Disparities - Data Science Pop-up Seattle

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  1. Keys to Understanding When You Are Looking for a Data Scientist vs. Engineer, and When and How to Utilize a Recruitment Firm Mary Kypreos Recruiting Manager for the Open Source & Big Data Team, Greythorn marykypreos GreythornNA #datapopupseattle

  2. UNSTRUCTURED D Data Science POP-UP in Seattle Produced by Domino Data Lab Domino’s enterprise data science platform is used by leading analytical organizations to increase productivity, enable collaboration, and publish models into production faster. #datapopupseattle www.dominodatalab.com

  3. Building(a(Data(Team Understanding(when(you(are( looking(for(a(data(scientist(versus(a( data(engineer,(and(when/how(to( use(a(recruiting(firm Mary(Kypreos,(Recruiting(Manager,(Big(Data(and(Open(Source(Team @marykypreos(((((((((((((linkedin.com/marykypreos

  4. Who(We(Are Our$Niche$ We(specialize(in(recruiting(for(startups(in(the(Big(Data(and( Open(Source(spaces—whether(that(is(a(data(scientist,(open( source(committers,(director(of(engineering,(etc.( Presence$in$the$Community$ Our(reputation(is(built(on(our(passion.(We(sponsor(local( meetups,(attend(national(conferences,(and(most( importantly,(learn(and(understand(what’s(being(said.(( The$Unicorn$ Our(Unicorn(logo(goes(all(the(way(back(to(our(first(client.( After(consistently(finding(them(Apache(Committers,(they( kept(emailing(asking(for(more(Unicorns.(Thus,(the(legend( was(born…( @MaryKypreos linkedin.com/MaryKypreos Greythorn.com

  5. My(Big(Data(Journey… Left(to(Right:( •CERN,(2008( •Seattle(Scalability,(2014( •OSCON,(2015( •Velocity,(2015 @MaryKypreos linkedin.com/MaryKypreos Greythorn.com

  6. Is(It(a(Data(Scientist? Too$Many$Options?$ Is(a(Data(Scientist(a(quant(in(finance,(a( researcher(in(science,(or(a(statistician(in( industry?(All(of(the(above!(There(is(no(one] size]fits]all(definition.(( In(“Analyzing(the(Analyzers,”(published(by( O’Reilly,(the(authors(argue(that(there(are(at( least(4(different(types(of(Data(Scientists:(( •((Data(Businesspeople( •((Data(Creatives( •((Data(Developers( •((Data(Researchers( Focus$on$Your$Problem$ Don’t(get(lost(in(titles(and(hype.(Instead( focus(on(the(skills(you(truly(need.(That’s( where(your(search(will(begin.(( @MaryKypreos linkedin.com/MaryKypreos Greythorn.com

  7. Understanding(Your(Needs ▪ Avoid(the(hype(at(all(costs—hire(for(your(needs(and( your(needs(alone.(( ▪ Knowing(the(bigger(picture(will(help(you(identify(your( needs(and(attract(the(right(talent @MaryKypreos linkedin.com/MaryKypreos Greythorn.com

  8. Data(Scientist:(Typical(Skills ▪ Pulls(insights(from(data(to( answer(questions(and(solve( problems( ▪ Creates(models(and(tells(a( story( ▪ Strong(in(the(scientific( process(and(handling( unknowns( ▪ Typically(advanced(degrees( ▪ Typically(scripting(versus( coding Source:(Drew(Conway @MaryKypreos linkedin.com/MaryKypreos Greythorn.com

  9. Data(Engineer:(Typical(Skills ▪ Focuses(on(systems(that(store/ retrieve(data( ▪ Builds(robust(databases( ▪ Typically(software(engineer(by( trade/education( ▪ Strong(engineering/programming( skills( ▪ Databases/data(warehouse( knowledge( ▪ Experience(with(big(data( technologies,(tools,(etc.(( @MaryKypreos linkedin.com/MaryKypreos Greythorn.com

  10. Navigating(the(In]Between Source:(Dataconomy Although(Data(Scientist(and(Data(Engineering(skills(can(overlap,(it’s(rare( to(find(someone(truly(strong(in(both(areas.(Not(to(mention,(someone( who(wants(to(do(both.( @MaryKypreos linkedin.com/MaryKypreos Greythorn.com

  11. Know(the(Position(Before(Interviewing Where$to$Start$ If(you(already(have(a(data(expert(on(staff,(they(will(be(key(to(your(hiring( If(you(aren’t(a(data(expert,(have(never(hired(a(data(expert,(or(don’t(already(have(data( experts(on(staff,(find(outside(assistance:( ▪ Consult(a(trusted(friend(or(advisor( ▪ Hire(an(agency( Never$Wing$It$ Do(not(use(your(interview(process(to( determine(who(or(what(you(need.( @MaryKypreos linkedin.com/MaryKypreos Greythorn.com

  12. If(You(Choose(an(Agency Interview$Them!$ If(you(are(interviewing(candidates(to(join(your(team,(why(wouldn’t(you(also(interview(the( agencies(finding(the(candidates(you(are(interviewing?( ▪ Have(they(placed(people(in(similar(roles?( ▪ Will(you(have(one(point(of(contact(or(multiple?( ▪ Check(their(references!( ▪ Does(their(personality(mesh(with(your(company’s(personality?( ▪ What’s(their(reputation(in(the(industry?( Don’t$Get$Stuck$on$Terms$ When(you(find(the(right(agency,(don’t(get(caught(up(on(the(terms.(As(always,(you(will(get(the( quality(of(the(work(you(pay(for,(so(pay(for(the(quality(you(want(and(you(won’t(regret.(( Limit$the$Number$of$Firms$You$Work$With$ Working(with(10(agencies(may(get(you(10x(the(resumes,(but(it(harms(the(power(of(your(brand.( Only(entrust(your(story(and(reputation(to(a(select(few(agencies(because(becoming(old(news( will(limit(your(access(to(the(talent(pool(you(need.(( @MaryKypreos linkedin.com/MaryKypreos Greythorn.com

  13. In(Short… If$You$ Know(what(you(want( Work(with(trusted(resources( Ensure(you(are(not(offending(the( community( Uphold(your(reputation( ▪ ▪ ▪ ▪ You’ll$have$better$access$to$the$type$of$ talent$you$want$to$hire$and$who$want$to$ work$with$you.$$ @MaryKypreos linkedin.com/MaryKypreos Greythorn.com

  14. Finding(the(Elusive(Flying(
 Rainbow]Unicorn]Cat If(you(are(an(active(or(passive(job( seeker,(email(Mary(Kypreos:( mary.kypreos@greythorn.com( If(you(are(a(company(seeking(hiring( help,(email(Lindsey(Thorne:( lindsey.thorne@greythorn.com( @MaryKypreos linkedin.com/MaryKypreos Greythorn.com

  15. @datapopup #datapopupseattle #datapopupseattle

  16. Thank You To Our Sponsors #datapopupseattle

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