Senior Data Scientist

About the Company

LinkedIn is the world’s largest professional networking platform, dedicated to creating economic opportunities globally. The company’s offerings enable individuals to build meaningful connections, explore career opportunities, develop critical skills, and gain insightful knowledge daily. LinkedIn also prioritizes investing in employee development and fosters a culture grounded in trust, inclusivity, and enjoyment to support success for all team members.

Role Overview

The Data Science team at LinkedIn harnesses large-scale data to guide business decisions and provide valuable insights, contributing to member engagement and corporate growth. Managing data from over a billion users, the team supports both B2B and B2C programs, presenting vast opportunities for professionals to impact and evolve their careers. The successful candidate will collaborate extensively across departments such as product, marketing, sales, engineering, policy, and operations to generate metrics, analyses, solutions, and actionable insights that inform business strategies.

Key Responsibilities

• Collaborate with various teams to help complete complex strategic initiatives across multiple organizational levels.
• Shape business and product direction through data-driven strategic presentations.
• Work alongside skilled data science experts and cross-departmental teams to identify new business prospects and optimize product strategies.
• Analyze extensive structured and unstructured datasets, performing deep analytical work and building machine learning models to enhance user value and customer outcomes.
• Create and maintain essential business metrics and develop automated dashboards and data visualizations to monitor and derive actionable insights.
• Design and evaluate experiments to test new product concepts or market strategies, providing clear recommendations based on outcomes.
• Partner with technology teams to build, prototype, and validate scalable data insight tools, including backend, frontend, and data components.
• Provide coaching and mentorship to junior data science team members.

Required Qualifications

• Bachelor’s degree in a quantitative field such as Computer Science, Statistics, Operations Research, Informatics, Engineering, Applied Mathematics, or Economics.
• Minimum three years of relevant industry or academic experience handling large datasets.
• Proven ability to influence strategic decision-making through compelling data presentations.
• Proficiency in SQL and at least one programming language like R, Python, or Scala.
• Competency in applied statistics and statistical modeling using software tools.
• Experience in storytelling with data and utilizing visualization platforms.
• Familiarity with experimental design and A/B testing methodologies.

Preferred Qualifications

• MS degree with three or more years of experience or PhD with one or more years of related experience involving extensive data analysis.
• Expertise handling large-scale structured and unstructured datasets.
• Working knowledge of Unix shell commands, version control tools such as git, and code review platforms.
• Experience working with government datasets or third-party public APIs.
• Strong communication skills, capable of simplifying complex problems for diverse audiences.

Compensation and Benefits

LinkedIn offers generous health and wellness initiatives alongside paid time off to promote well-being for employees and their families. The role’s base salary ranges from $121,000 to $198,000 annually, with total compensation potentially including performance bonuses, stock incentives, and other benefits. Compensation varies based on skills, experience, certifications, and location specifics.

Additional Information

LinkedIn is an equal opportunity employer committed to diversity and inclusion. The company provides reasonable accommodations for applicants with disabilities to ensure full accessibility during the job application and interview processes.

LinkedIn follows pay transparency principles as a federal contractor and complies with relevant employment regulations including fair hiring practices and non-discrimination policies. Applicants with arrest or conviction records are considered in accordance with applicable laws.