Ba Summer Princeton Presentation

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<ul><li><p> 1 </p><p> Business Analytics Department Presentation to Princeton Data Science February 19, 2015 </p><p> Data Science at </p></li><li><p> 2 </p><p>1. Introduction 2. About Linkedin. Products and the Data. 3. The Business Analytics Team at Linkedin 4. Tools and skills 5. Example work, including past summer interns 6. The challenge &amp; opportunity with our data 7. Summer internships </p><p>Agenda </p></li><li><p> 3 </p><p>Some inspiration. Moneyball Story &amp; Data Science </p></li><li><p> 4 </p><p>Our vision is to create economic opportunity for every member </p><p>of the global workforce. </p><p>4 </p><p>Jeff Weiner, CEO Linkedin </p></li><li><p> 5 </p><p>Our mission is to connect the worlds professionals to make them more </p><p>productive and successful. </p><p>5 </p><p>Jeff Weiner CEO Linkin </p></li><li><p> 6 </p><p>Members 347,000,000+ </p></li><li><p> 7 </p><p>3,500,000+ Companies </p></li><li><p> 8 </p><p>1,500,000+ Jobs </p></li><li><p> 9 </p><p>Linkedin Company facts ! Silicon Valley Roots </p><p>! Founded by Reid Hoffman and 4 cofounders in 2002 ! Site officially launched in 2003. 4,500 members at end of month 1 ! The company is publically held ! Diversified businesses: talent, marketing, sales, premium </p><p>subscriptions ! HQ in Mountain View, CA, with offices in 30 cities around the world ! Linkedin is available in 23 languages ! Linkedin has more than 6,000 full time employees </p><p>Now: Its like a billion dollar startup Revenue: &gt;$2bil/year All time high stock price just today, Feb 6 </p></li><li><p> 10 </p><p>Linkedin Woldwide Membership </p><p>! Largest professional network in the world ! Over 347 million members in over 200 countries &amp; territories ! Professionals are signing up at a rate 2 members per second. ! In Q3 2014, 75% of new members came from outside the US. ! Over 39 million students and recent college graduates. </p></li><li><p> 11 </p></li><li><p> 12 </p><p>Linkedins free products for members </p><p>The professional profile of record </p><p>Connect all of the worlds professionals </p><p>The definitive professional </p><p>publishing platform </p><p>Identity Network Knowledge </p></li><li><p> 13 </p><p>Opportunity </p><p>Identity Network Knowledge </p><p>Company pages, Job postings, your connections </p><p>to those companies </p><p>Company Pages </p></li><li><p> 14 </p><p>University Pages </p><p>Identity Network </p></li><li><p> 15 </p><p>Enable passive recruiting at </p><p>massive scale </p><p>Identify and engage professionals with relevant content </p><p>Transform cold calls into warm </p><p>prospects </p><p>Hire Market Sell </p><p>How do we make money? Linkedin Business Lines for B2B customers </p></li><li><p> 16 </p></li><li><p> 17 </p><p>Critical mass of dataRelevant and valuable products and services</p><p>Technologyplatform</p><p>Member growth and engagement</p><p>LinkedIns business model &amp; why analytics is important </p></li><li><p> 18 </p><p>LinkedIn has a Unique Mix of B2C and B2B Business</p><p>B2C Business to Consumer</p><p>B2BBusiness to Business</p><p>Analytics is the key to bridge the gap</p></li><li><p> 19 </p><p>Where is BA in the organization? </p><p>Business Analytics </p><p>Business Operations &amp; Analytics </p><p>CFO </p><p>CEO </p></li><li><p> 20 </p><p>Provide the best-in-class end-to-end analytic solutions to power internal LinkedIn teams to </p><p>be more productive and successful! </p><p>Business Analytics Team Mission </p></li><li><p> 21 </p><p>Biz Analytics</p><p>Team $Engineering</p><p>GlobalSales</p><p>OrganizationOperationsSales Ops,</p><p>Ad Ops,Biz Ops</p><p>Team $Product</p><p>GlobalCustomer </p><p>OrganizationMarketing</p><p>Talent Solutions</p><p>Marketing Solutions</p><p>60+ team members support 6000+ internal employees</p><p>SalesSolutions</p><p>PremiumSubscriptions</p><p>ConsumerMarketing</p></li><li><p> 22 </p><p>InsightsWhat is the best </p><p>that could happen?</p><p>IntelligenceWhat will happen?</p><p>Information/KnowledgeWhy did it happen?</p><p>DataWhat happened?</p><p>Business ROI</p><p> Business analytics evolution: from data to insights</p></li><li><p> 23 </p><p>Playing below the water level</p></li><li><p> 24 </p><p> Our goal is always: Results &amp; Change</p></li><li><p> 25 </p><p>Business Analytics teams majors at university </p><p>Artificial Intelligence Atmospheric &amp; Oceanic Sciences Biomedical Informatics Chemical Engineering Computational Biology Computer Engineering Computer Science Economics Electrical and Electronics Engineering Finance French Human Computer Interaction International Relations </p><p>Machine Learning Marketing Materials Engineering Mathematics Mechanical Engineering Medicine Operations Research Philosophy Physics Political Science Psychology Quantitative Finance Quantum Physics Statistics Systems Engineering </p></li><li><p> 26 </p><p>Business Analytics teams previous job titles </p><p>Applied Scientist Assistant Professor BI Consultant Business Analyst Business Systems Analyst Co-Founder CTO Data Scientist Derivatives Trader Economic Analyst Engine engineer Financial Engineer Founder Fraud Specialist Java Architect Lead Singer </p><p>Marketing analyst Mechanical engineer Neuro Surgeon Physicist Product Manager Risk Analyst Scrum Master Search Engineer Software Engineer Statistician Teaching Assistant Trader UX Designer Vice President VLSI Design Engineer Web and Product Analyst </p></li><li><p> 27 </p><p>Business models Marketing, Sales, Recruiting Targetting &amp; Attribution Customer experience Communication/interpersonal skills </p><p>Statistics Probability Optimization Modeling Simulations Analytics A-B Testing </p><p>R, Python, Java, PHP, SPSS, Javascript HTML, Web Tableau, Data Vis Machine Learning APIs, ETL SQL, Hadoop, Hive, Pig, Data products </p><p>The Complete Data Scientist </p></li><li><p> 28 </p><p>Three Major Data Dimensions @ LinkedIn</p><p>SocialBehaviorIdentity</p></li><li><p> 29 </p><p>Web API </p><p> The technology powers E2E analytics</p><p>Petabytes </p><p>Gigabytes Megabytes </p><p>Terabytes </p><p>1 </p><p>2 </p><p>3 4 </p><p>Data Visualization Data ELT and Aggregation </p><p>Analytics Portal </p><p>Kilobytes 5 </p></li><li><p> 30 </p><p>Machine Learning Techniques Commonly Used by the </p><p>Business Analytics Team </p><p> Random Forest Generalized Boosted Models (GBM) Logistic Regression Decision Trees Stochastic Gradient Descent(SGD) Clustering Bayesian Networks Text Classification &amp; Mining (LDA, NLP) </p></li><li><p> 31 </p><p>Propensity Now Accounts for 56% of Total Marketing Acquisitions</p><p>Monthly subscription marketing acquisitionOnline sourcing business</p><p>Total Prediction Power</p><p>Propensity Model</p><p>56% </p><p>Signal Based Marketing</p><p>34% </p><p>Profile Based Marketing</p><p>10% 10%</p><p>34%</p><p>56%</p><p>100%</p></li><li><p> 32 </p><p>Past Summer Intern Examples </p></li><li><p> 33 </p><p>Past Summer Intern Examples </p></li><li><p> 34 </p><p>Past Summer Intern Examples </p></li><li><p> 35 </p><p>Past Summer Intern Examples </p></li><li><p> 36 </p><p>Past Summer Intern Examples </p></li><li><p> 37 </p><p>Past Summer Intern Examples </p></li><li><p> 38 </p><p>Past Summer Intern Examples </p></li><li><p> 39 </p><p>Past Summer Intern Examples </p></li><li><p> 40 </p><p>Past Summer Intern Examples </p></li><li><p> 41 </p><p>Thought Exercise: What could you build if you had </p><p>Member Name Location Work History 1 Job title Start date, End date Company Name Work History 2 Job title Start date, End date Company Name Skills School &amp; Major </p><p>Company A Name Location Industry Employees Employees with Linkedin profiles Job openings </p><p>Company B Company Name Location Industry Employees Employees with Linkedin profiles Job openings </p></li><li><p> 42 </p><p>Benefits of a Summer Internship at Linkedin! San Francisco ! and the Silicon Valley !! Company-sponsored Housing and Relocation! Competitive Wages! Full Tech Support! Extensive Health &amp; Wellness program (fitness and meals)! Social Activities! Transform yourself, the company, the world</p></li><li><p> 43 </p><p>"I went from our alumni site on Linkedin and looked at the density of data they had on every one of the alum. Then I started digging and digging and digging in LinkedIn and realized, it's not a human resource company, it's a data company.</p><p>! Ann Windblad, January 2015! Venture Capitalist, Hummer Winblad Venture Partners! (funded Napster in 2000)</p></li><li><p> 44 </p><p>Hire the right people with the right </p><p>5%15%</p><p>100%80%</p><p>Skills + IQ &amp; EQ + Passion = Good Analyst Great Analyst? </p><p>? </p><p>0% </p><p>+X % </p></li><li><p> 45 </p><p>We are hiring!Want to Know the Answer? Please Join LinkedIn! </p></li><li><p> 46 </p><p>4 - 2015 Summer Internship Openings in BA </p></li></ul>


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