Staff Data Scientist

LinkedIn is the world’s largest professional network, focused on creating economic opportunity for members of the global workforce. As a Staff Data Scientist, you will lead large-scale, data-driven initiatives that shape product and business strategy through metrics, analyses, and machine learning, partnering with cross-functional teams to drive engagement, growth, and monetization.

• Partner with cross-functional teams (product, marketing, sales, engineering, policy, operations) to initiate, lead, and deliver large-scale strategic data science projects end-to-end.
• Act as a thought partner to senior leaders to prioritize and scope work, provide recommendations, and evangelize data-driven decision-making aligned to strategic goals.
• Analyze large-scale structured and unstructured data; build deep-dive analyses and machine learning models to improve member value and customer success.
• Define and develop core business and product metrics; build automated dashboards and visualizations to monitor performance and generate insights.
• Design, run, and analyze experiments (e.g., A/B tests) to evaluate new product ideas and go-to-market strategies; translate results into actionable recommendations and narratives.
• Deliver data-centric presentations that influence org-wide product and business strategy.
• Collaborate with technology partners to prototype and validate scalable tools/applications (backend, frontend, and data) that convert data into insights.
• Provide technical guidance, mentorship, and code/design reviews to junior team members.

• Bachelor’s degree or higher in a quantitative discipline (e.g., statistics, operations research, computer science, engineering, applied mathematics, economics, informatics).
• 5+ years of relevant work experience.
• Strong SQL skills.
• Proficiency in at least one programming language (e.g., Python, R, Scala).
• Experience in applied statistics and statistical modeling using statistical software.
• Experience with data visualization tools and communicating insights via data storytelling.
• Experience designing and running platform experiments (including A/B testing).
• Preferred: experience working with massive-scale structured and unstructured data.
• Preferred: high-quality, optimized coding practices and experience coaching others; familiarity with Unix shell, git, and formal code review processes.
• Preferred: experience using government data or third-party/public APIs.
• Preferred: demonstrated mentorship of other data scientists; strong communication skills with executive-level audiences.

• Work model: Hybrid (work from home and from a LinkedIn office on select days based on business needs).
• Benefits: Health and wellness programs and time away; total compensation may include annual bonus, stock, and additional benefits.
• Compensation: Pay range stated as $144,000–$236,000 annually (varies by candidate factors and location).