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Linkedin is Hiring Data Scientist


Data Scientist | Responsibilities | Qualifications | Linkedin

Table of Content
About Company
Job Description
Prefered Qualifications
Reequired Qualifications
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About Company

Founded in 2003, LinkedIn connects the world’s professionals to make them more productive and successful. With more than 756 million members worldwide, including executives from every Fortune 500 company, LinkedIn is the world’s largest professional network. The company has a diversified business model with revenue coming from Talent Solutions, Marketing Solutions, Sales Solutions and Premium Subscriptions products. Headquartered in Silicon Valley, LinkedIn has offices across the globe.

Job Description

inkedIn 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 Data Science team leverages big data to empower business decisions. Trust data science team at LinkedIn works in close partnership with the trust engineering and product team to identify opportunities to develop and enhance LinkedIn member experiences. A few examples include: optimize member account access experience while defending attacks, provide insights to improve feed content quality on site, analyze trust/security features’ performance through product A/B testing, etc.

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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 managers, engineers, designers, product marketing, and the trust infrastructure team to provide deep insights and actionable recommendations to drive LinkedIn’s Trust and Security. A successful candidate will be both technically strong 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 product managers to identify business opportunities and optimize member experiences at LinkedIn.
  • Reporting and Monitoring: Design, create and automate reports and dashboards to track key business metrics in security Engineering and security product areas. ETL data, clean and validate data when needed.
  • Product Analytics: Design and analyze experiments to test new product/feature ideas and convert the results into actionable business recommendations. Formulate success metrics for initiatives, create and automate dashboards/reports to monitor them and quickly identify the root cause of the anomaly.
  • End-to-end Deep Dive Analytics: Deep dive into an area, find insights and understand the root cause of an observed trend, and translate the insights into actionable recommendations. When applicable, implement the solution and monitor the performance. Analyze and mine both structured and unstructured data to drive member-centric insights.
  • Develop and improve predictive models to optimize user experience and operational efficiency.
  • Enable others in the organization to utilize your work by onboarding new metrics into our self-serve data system and experimentation platform.
  • Craft compelling stories; make logical recommendations; drive informed actions.
  • Explain complex problems to a variety of audience; Drive meetings and lead discussions.
  • Perform ad-hoc analysis at a timely manner

Basic Qualifications

3+ years relevant industry or relevant academia experience in Analytics/Data Science working with large amounts of data.
Experience with SQL/Relational databases
Experience with data visualization tools (eg. Tableau, BI dashboarding, R visualization packages, etc.)
Experience in data analysis in Spark/HDFS and Scala/Hive
Experience running platform experiments and techniques like A/B testing

Prefered Qualifications

  • Relevant experiences in security analytics, risk analytics, trust & safety analytics from high tech companies
  • Experience in applied statistics and statistical modeling in at least one statistical software package, (eg. R, SPSS)
  • Advanced degree in quantitative fields – Computer Science, Engineering, Operational Research, mathematics, Statistics, Economics, etc.
  • Strong analytical skills
  • Strong business mindset and strong problem-solving skills
  • Excellent communications skills. Candidate should be able to explain complex problems to a variety of audiences. Candidate should be able to drive meetings and lead discussions