Staff, Analytics - LinkedIn Careers
Posted: February 17, 2017
Reference ID: 298319091
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LinkedIn's Analytics team leverages big data to empower business decisions. Our team is rapidly reinventing the way that proprietary data can drive sales / marketing efforts and product strategies. We are now looking for a talented and driven individual to accelerate our efforts and be a major part of our data-centric culture. This person will work closely with product, engineers, marketing, and infrastructure team to provide deep insights and actionable recommendations for the Careers team. A successful candidate will be both technically strong and business savvy, with a passion to make an impact through creative storytelling and timely actions.
Responsibilities: Overall, a highly driven, results-oriented, creative and nimble problem solver with a willingness to do 'whatever it takes' to deliver business impact quickly. Ability to prioritize and set direction in a fast moving environment. Work with a team of high - performing analytics professionals and product managers to identify business opportunities and optimize product performance/engagement. Own end-to-end product analytics. Analyze and mine both structured and unstructured data to drive product centric as well as user-centric insights. Craft compelling stories; make logical recommendations; drive informed actions. Be a thought partner to product managers in making data-driven business decisions. Create insightful automated dashboards and data visualizations to track key business metrics.
Basic Qualifications: BS + 6 years of industry experience OR MS + 5 years of industry experience Degree in quantitative fields - Computer Science, Engineering, Mathematics, Operations Research, Statistics, Economics, or related fields. Experience with SQL (Teradata, Oracle, etc) and querying from Hadoop (Pig, Hive). Experience working with statistical analysis software such as R, SPSS, SAS, etc.
Preferred Qualifications: BS + 8 years of industry experience OR MS + 7 years of industry experience, ideally within the relevant domain of product analytics. Degree in quantitative fields - Computer Science, Engineering, Mathematics, Operations Research, Statistics, Economics, or related fields. Strong technical skills in querying against and transforming big data within both Hadoop HDFS system and relational databases. Fluency in a statistical analysis software such as R, SPSS, SAS, etc. Fluency in a scripting language such as Python, PERL, RUBY, etc. Excellent communications skills, with the ability to synthesize, simplify and explain complex problems to different types of audience.