Data & Business Intelligence, Sr. Associate at LinkedIn3

This role can be based in Sunnyvale, San Francisco, New York, or Chicago. 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. We’re seeking a Senior Associate, Data & Business Intelligence to join our team. In this role, you’ll help build and scale the data environment that powers Sales Operations at LinkedIn, while developing solutions that drive impactful, data-informed decisions. You’ll work on complex analytics initiatives across LinkedIn Talent Solutions (LTS) and LinkedIn Sales Solutions (LSS), leveraging tools and skills such as SQL, Spark, and advanced analytics techniques. This role is ideal for someone passionate about strengthening data infrastructure and enabling scalable, high-quality insights. Success in this role is driven by cross-functional collaboration with business leaders, Engineering, Sales, and Operations, paired with clear communication and the ability to navigate complex, high-impact work in a fast-paced environment, delivering timely, actionable insights while building a reliable foundation for data-driven decision-making. Responsibilities:  • Leverage LinkedIn’s unique data to create innovative analyses & dashboards, including developing/deploying predictive models (e.g., forecasting and classification). • Write SQL/Python queries to extract necessary data, analyze the results to generate actionable insights and present the findings. • Collaborate closely with the sales, marketing, engineering and data teams to provide analysis, reporting and tools that inform key stakeholders. • Build cross-functional relationships and partner effectively with other teams to drive project success. • Make business recommendations, conveying findings at multiple levels including managers and peers through visual displays of quantitative information.