Staff Data Scientist - Content Experience Editorial Products, Consumer Analytics
Posted: December 17, 2016
Reference ID: 214035579
LinkedIn was built to help professionals achieve more in their careers, and every day millions of people use our products to stay informed, stay connected, discover opportunities and gain insights. Our global reach means we get to make a direct impact on the world's workforce in ways no other company can. We're much more than a digital resume - we transform lives through innovative products and technology. Searching for your dream job? At LinkedIn, we strive to help our employees find passion and purpose. Join us in changing the way the world works.
Consumer Analytics team: The Consumer Analytics team at LinkedIn works in close partnership with the Product team to identify opportunities to develop and enhance products and features. We use our rich member data to measure, understand and improve our products. Each data scientist on our team embeds within a product team and works closely with product managers, engineers, editors, designers and a cross-functional team to drive LinkedIn's core Content Experience products, such as our Publishing platform and Feed. These products are core to LinkedIn's everyday use case, and the first content members interact with when they come to LinkedIn - join us in ensuring they get and create the news and insights they need as soon as they log on to LinkedIn. You'll be a part of the larger Consumer Analytics team, where you'll have the opportunity to work with some of the best data people anywhere in an environment that truly values data-driven decisions.
We are looking for a Staff Data Scientist to join our team. This particular role will work closely with our unique editorial team: a group of reporters and editors with experience at some of the world's top business publications who curate, create and cultivate the 150k+ weekly posts, millions of weekly shares and other insights that stream through Linkedin. The team also creates the LinkedIn Lists franchise, a series of unrivaled lists that use LinkedIn data and editorial input to surface the companies and people professionals should be following, hiring and working for. The edit team is based out of NYC, but editors are also located in SF, London, Paris, Munich, Bangalore and more. This is a true human-and-machine system - one not found at any other social networks or publication - and each side helps train the other. The data scientist will be a key driver in making this real-time operation perform even faster and better and will be responsible for informing business and product strategy and decisions.
Extract and analyze LinkedIn data to derive actionable insights Formulate success metrics for completely novel products or business areas, socializing them and creating dashboards/reports to monitor them Create the framework for each LinkedIn List, from "Next Wave: Top Professionals Under 35" to "Top Attractors: Where the World Wants to Work Now. " How do we utilize LinkedIn's amazing data to surface the top companies and people worth writing about and following? No other data-informed lists like these exist; you'll be helping to craft the playbook. Design and analyze experiments to test new product ideas and convert the results into actionable product recommendations As an end consumer of the data, determine the tracking necessary to enable analytics of our products and features by working closely with product and engineering partners Enable others in the organization to utilize your work by onboarding new metrics into our self-serve data system and experimentation platform Develop models and data-driven solutions that add material lift to principal performance metrics Provide technical guidance to other team members Exploratory data analysis with the goal of product ideation, prototyping, and developing new and innovative features that can drive additional value for/engagement from our members Communicate the results of your work, to evangelize data-driven product innovation - both inside and outside of LinkedIn. Basic Qualifications:
BS/MS degree in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc. 4+ years' industry experience working with large amounts of real data with SQL (Teradata, Oracle, or MySQL) and R, or other statistical package 4+ years' industry experience providing analytical insights and business reports to product or business functions Preferred Qualifications:
Experience in Hadoop or other MapReduce paradigms and associated languages such as Pig, Sawzall, etc. 5+ years of experience programming in Java or Python and working with large datasets Experience presenting insights to executive staff on a regular basis Experience in the publishing industry or a deep understanding of media Expertise in applied statistics and in at least one statistical software package, preferably R Proficiency in SQL and in a Unix/Linux environment for automating processes with shell scripting Ability to communicate findings clearly to both technical and non-technical audiences Ability to translate business objectives into actionable analyses PhD in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.