LinkedIn was built to help professionals achieve more in their careers, and every day millions of people use our products to make connections, 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.
LinkedIn’s Analytics team leverages big data to empower business decisions and deliver data-driven insights, metrics, and tools in order to drive member engagement, business growth, and monetization efforts. With over 500 million members around the world, a focus on great user experience, and a mix of B2B and B2C programs, a career at LinkedIn offers countless ways for an ambitious data scientist to have an impact.
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 various cross-functional teams such as product, marketing, sales, engineering and operation to develop and deliver metrics, analyses, solutions, and insights, with actionable recommendations to business partners. Successful candidates will exhibit technical acumen and business savvy, with a passion for making an impact through creative storytelling and timely actions.
Work with a team of high-performing analytics, data science professionals, and cross-functional teams to identify business opportunities, optimize product performance or go to market strategy.
Analyze large-scale structured and unstructured data; develop deep-dive analyses and machine learning models to drive member value and customer success.
Design and develop core business metrics, create insightful automated dashboards and data visualization to track them and extract useful business insights
Design and analyze experiments to test new product ideas or go to market strategies. Convert the results into actionable recommendations.
Craft compelling stories; make logical recommendations; drive informed actions.
Engage with internal technology partners to prototype and validate tools developed in-house for near-real-time processing of very large datasets
Initiate and drive projects to completion with minimal guidance
Communicate findings to senior leaders and evangelize data-driven business decisions
Bachelor or higher degree in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.
Bachelors with 5+ years of industry experience or Masters with 3+ years of industry experience
Proven record with SQL and relational database query performance.
Background in at least one programming language (e.g., R, Python, Java, Ruby, or Perl)
Experience in appliedstatistics and statistical modeling in at least one statistical software package, preferably R
Experience with data visualization tools (eg. Tableau, BI dashboarding, R visualization packages, etc.)
Masters or PhD degree in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.
Experience with manipulating massive-scale structured and unstructured data.
Experience with Hadoop or other MapReduce paradigms, and associated languages such as Pig, Hive, etc.
Working knowledge of Unix and Unix-like systems, git and review board.
Excellent communications skills, with the ability to synthesize, simplify and explain complex problems to different types of audience, including executives