LinkedIn is the world’s largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed.

Join us to transform the way the world works.

LinkedIn member data is amazingly rich and provides a fantastic opportunity for Data Scientists to explore and create, ultimately developing ways for members to improve their professional lives. You will have the opportunity to work with some of the best data people anywhere in an environment that truly values data-driven decisions.

About the team -
The Trust Data Science team at LinkedIn works in close partnership with the trust engineering, content moderator  and product teams to identify opportunities to develop and enhance LinkedIn member experiences. A few examples include: enabling our trust & security team (content reviewers) to be effective through data driven insights and minimize damage to our members, 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.

You will have the opportunity to work with and lead highly passionate data scientists, as well as our brilliant cross-functional partner teams in Engineering, Product Management, and Design. Together, we are creating immense economic value for our customers using the largest global professional economic graph.

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.

Responsibilities:

• We inform product strategy, influence the product roadmap, and guide product decisions by
• Accessing and analyzing the world's richest professional data to generate insights and make proactive recommendations.
• Formulating success metrics for completely novel products and creating dashboards/reports to monitor them.
• Designing and analyzing experiments to test new product ideas.
• Developing models and data-driven solutions that add material lift to principal performance metrics.

Basic Qualifications:

• BS/MS in a quantitative discipline: Statistics, Applied Mathematics, Operations Research, Computer Science, Engineering, Economics, etc.
• 10+ years of experience working with large amounts of real data with SQL (Teradata, Oracle, or MySQL) and R, or other statistical package.
• 10+ years of experience in a Unix/Linux environment for automating processes with shell scripting.

Preferred Qualifications:

• Experience with Consumer Internet products.
• Experience programming in Python, Java, or another programming language - Pig experience desired.
• Ability to translate business objectives into actionable analyses.
• Ability to communicate findings clearly to both technical and non-technical audiences
• Knowledge in one of the following areas is a strong plus: Viral Growth mechanisms, user acquisition in International markets, Search Engine Optimization (SEO)
• Expertise in applied statistics, understanding of controlled experiments.
• Cross-cultural background and experience

Suggested Skills:

• Sql
• Data visualization
• Hive

India Disability Policy 

LinkedIn is an equal employment opportunity employer offering opportunities to all job seekers, including individuals with disabilities. For more information on our equal opportunity policy, please visit https://legal.linkedin.com/content/dam/legal/Policy_India_EqualOppPWD_9-12-2023.pdf

Global Data Privacy Notice for Job Candidates ​

Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal.