Insights Program Manager - AI Infrastructure

Job Description

This role will be based in San Francisco, Sunnyvale, New York City, or Chicago.

At Linked In, 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 Linked In office on select days, as determined by the business needs of the team.

At Linked In, we empower professionals worldwide to achieve more. Every day, millions of people use our products to connect, discover opportunities, and gain valuable insights. As an Insights Program Manager, you'll play a key role in helping Linked In and our customers make smarter, data-driven decisions by transforming complex data into actionable insights that drive business outcomes across our Talent Solutions organization.

This role sits at the unique intersection of Linked In product expertise, proprietary data, and go-to-market strategy. You'll combine technical program management, analytical problem-solving, and cross-functional leadership to develop scalable insights programs and solutions that influence decisions across product, marketing, sales, and operations.

As an Insights Program Manager, you'll own the development and delivery of high-quality, reliable insights, translating Linked In's rich datasets into strategic recommendations that create measurable impact. You'll also help advance automation and AI-driven capabilities, leveraging tools such as Large Language Models, prompt engineering, and scalable data solutions to improve how insights are generated and delivered, ultimately enhancing the value Linked In provides to customers.

• Data-Driven Insights Development
  • Leverage Linked In’s proprietary datasets to design and deliver impactful, scalable insights that align with product and marketing strategies addressing customer pain points and value propositions.
  • Write, review, and optimize code (SQL, Python, Spark SQL) to extract, process, and analyze data.
  • Oversee and maintain automated data pipelines and multiproduct workflows using tools such as Apache Airflow, HDFS, and internal platforms.
  • Integrate GenAI and LLM-based solutions (e.g., prompt engineering, summarization, and categorization) into insights pipelines for improved efficiency and scalability.
• Collaboration and Alignment
  • Partner with cross-functional teams, including Sales, Marketing, and Data Science, to refine messaging and enhance customer value delivery anchored in data.
  • Act as a strategic advisor to stakeholders, guiding the adoption of actionable, AI-enabled insights and ensuring program alignment with go-to-market priorities.
  • Establish strong stakeholder relationships, serving as a technical and strategic advisor for internal and external partners on program strategy.
• Insights Strategy and Vision
  • Define and execute the long-term vision and roadmap for your programs.
  • Identify gaps in existing tools and GTM motions, prioritize opportunities, and drive alignment on strategic initiatives.
  • Own end-to-end delivery of cross-functional programs such as campaign experimentation, actionable insights for driving product adoption, and thought leadership, balancing business goals with data and technical feasibility.
  • Measure the effectiveness of Insights driven interventions across our customer and field partner touchpoints and its impact on Linked In’s Talent business outcomes.
• Visualization and Communication
  • Develop compelling visualizations and narratives using Python, Tableau, or equivalent tools to communicate insights, synthesizing technical findings into clear business terms for executive and non-technical audiences to drive clarity and alignment.
  • Contribute to storytelling and content strategy for high-visibility initiatives, ensuring consistency with Linked In’s data narrative.
• Data Quality and Governance
  • Implement data quality checks to ensure accuracy, consistency, and integrity.
  • Drive standardization and best practices for insights pipeline governance, including version control (Git Hub) and documentation.
  • Champion responsible AI and data privacy practices in insights development.

Basic…