美国留学数据科学(DS)专业介绍和文书写作

2018时代兴华留学泛商科专业申请系列讲座主讲人：时代兴华海外导师团成员Frank数据科学（DS）专业介绍和文书写作2个人背景•清华工科本科•斯坦福大学金融工程和计算机科学双硕士，机械工程博士•申请美国研究生院收获全奖PhDOffers：Stanford（1)，MIT(2)，UCBerkeley(3)，Cornell(5)，GeorgiaTech(7)Duke，Northwestern(12)，UCLA(10)，UIUC(8)•工科USNews排名前七学校申了五个，拿到五个offer•Stanford，UCLA，Northwestern给了校长级的Fellowship•12月初拿到宾州州立offer，为当年北大清华秋季申请第一个博士全奖offer，轰动水木清华BBS飞跃重洋版•长期兼职从事留学咨询工作，时代兴华兼职咨询师•2017-2018年度学生收获排名前30的offer共计98枚！，横跨哈佛，斯坦福，康奈尔，CMU，布朗，杜克，纽约，普林斯顿，伯克利，哥大，密歇根，佐治亚理工，明尼苏达，UCLA等几乎所有名校。目录页•数据科学专业概论•数据科学在商科的应用领域•Finance / Marketing / Supply Chain / HR•数据科学核心技能•综述•技术技能（Math & Statistics / Programming / Database / Machine Learning / Data Mining / Data Cleaning / Visualization / 数学建模）•Soft Skills （Ethics / Problem Solving / Communication / Critical Thinking / Ask right questions / 学习能力）•申请材料包装技巧•Coursework / Course Projects / Research Experience / Internship数据科学专业概论-什么是大数据•Population increasing•We produce more data, especially with internet activity (very important)•We value these data. we know now how it can be useful (in terms of business, science, medical concerns, etc.) to collect data. Therefore, much effort is put in collecting/storing data from any source.•Finally, we now have access to huge databases from various sources : images, texts, internet activity, MRI from medicine, weather…大数据科学的主要任务：•Making use of big data: storing, manipulating, mining, analysing•It leads to dozen of new appealing: data scientist, data miner, data analyst… etc.原始驱动力：数据科学专业概论-大数据vs传统研究方式Step 1: Propose a physical model （最难的一步）Step 2: Test it on experimentationStep 3: While the model is not failing to provide good prediction, keep it.Step 1: Run enough experiments and collect dataStep 2: 直接从数据中分析出patterns即使无法解释这些patterns是怎么来的，也可以使用传统的研究方式基于大数据的研究方式数据科学在商科应用-FinancePart I：Investment Banking （主要是买方市场，如hedge fund）•Algorithmic trading （又名High Frequency Trading，极其在意算法效率）•Price trend prediction (time series analysis)•Key performance indicator prediction (volatility, Sharpe ratio, ROI, etc)数据科学在商科应用–Finance （Cont.）Part II：Consumer Retail Finance•Default prediction, e.g., anti money laundering, credit card fraud, insider trading （Credit Division）•Forecast expected loss / Risk management of assets （Risk Division）•Customer profiling, credit scoring, acquisition, retention, personalized services (Marketing Division)数据科学在商科应用–MarketingMoreclearlydefineyouridealcustomer.Inthepast,marketersfrequentlyhadtomakebestguessesastothedemographicsoftheiridealmarketsegment,butthatisnolongerthecase.Withbigdata,companiescaneasilyseeexactlywhoisbuyingandteaseoutevenmoredetailsabouttheircustomers,includingthingslikewhichwebsitestheyfrequent,whichsocialmediachannelstheyuse,andevenwhichbuttonstheyclickwhileonawebsite.Optimizecustomerengagement.Datacanprovideinsightsintowhoyourcustomersare,wheretheyare,whattheywant,howoftentheymakeapurchase,whenandhowtheyprefertobecontacted,andmanyotherimportantfactors.Companiesalsocananalyzehowusersinteractwiththeirwebsite–oreventheirphysicalstore–toimprovetheuserexperience.Improvecustomerretentionandloyalty.Manyretailershaveimplemented“loyaltycard”systemsthattrackacustomer’spurchases,butthesesystemsalsocantrackwhichincentivesandpromotionsaremosteffectiveinencouragingacustomer–individualcustomersaswellastheoverallgroupofcustomers–tomakeanotherpurchase.数据科学在商科应用–Marketing （Cont.）Marketingoptimizationandperformance.Withtraditionaladvertising,it’sdifficulttotrackimpactandreturnoninvestmentdirectly.Butbigdatacanhelpcompaniestomakeoptimalmarketingbuysacrossmanydifferentchannelsandtocontinuouslyoptimizetheirmarketingeffortsthroughtesting,measurement,andanalysis.Budgetmanagement.Becausebigdataenablescompaniestomonitorandoptimizetheirmarketingcampaignsforperformance,thatmeanstheycanbetterallocatetheirmarketingbudgetsforthehighestROI.Real-timepersonalization.Bigdatacombinedwithmachinelearningalgorithmsgivesmarketerstheopportunitytopersonalizetheirofferstoindividualcustomersinrealtime.Thinkaboutthe“customersalsobought”sectionofAmazonorthelistofrecommendedmoviesandTVshowsfromNetflix.Companiescanpersonalizewhatproductsandpromotionsaparticularcustomersees,evendowntosendingpersonalizedcouponsandofferstoacustomer’sphonewhenhewalksintoaphysicallocation.数据科学在商科应用–Marketing （Cont.）Marketresearch.Companiescanconductqualitativeandquantitativemarketresearchmuchmorequicklyandinexpensivelythaneverbefore.Onlinesurveytoolsmeanthatfocusgroupsandcustomerfeedbackareeasyandinexpensivetoimplement,anddataanalyticsmaketheresultseasiertoparseandtakeactionon.Reputationmanagement.Withbigdata,companiescaneasilymonitormentionsoftheirbrandacrossmanydifferentwebsitesandsocialchannelstofindunfilteredopinions,reviews,andtestimonialsabouttheirorganizationandproducts.Thesavviestcanalsousesocialmediatoprovidecustomerserviceandcreateatrustworthybrandpresence.Competitoranalysis.Newsocialmonitoringtoolsmakeiteasytocollectandanalyzedataaboutcompetitorsandtheirmarketingeffortsaswell.Thecompaniesthatcanusethisinformationwillhaveadistinctcompetitiveadvantage.DS在商科应用–Supply Chain Management1. Demand