Data Insights – Tech Manager – IC4

LinkedIn•San Francisco, CA

3d•Hybrid

About The Position

The Tech & Analytics team builds the analytical and automation foundation that powers LinkedIn's most important Go-to-Market decisions. We partner across Sales, Customer Success, Marketing, and Engineering to create a unified understanding of GTM performance. Our mission is to transform data into proactive insights and intelligent systems that guide LinkedIn's growth and efficiency. As a Data Insights Tech Lead, you are the technical authority and chief architect for the next generation of our GTM data solutions. This is a hands-on role for a senior IC who will spend a significant portion of their time architecting solutions, writing production-grade code, and mentoring junior data scientists and analytics engineers. You will be responsible for the end-to-end technical lifecycle of our most complex projects, from prototyping new AI-driven concepts to deploying scalable, automated systems. You will combine the analytical depth of a principal data scientist with the strategic storytelling needed to influence GTM leadership. Your primary goal is to architect and build the agentic workflows, predictive models, and automated systems that will fundamentally change how our GTM teams operate.

Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, Statistics, Physics, Economics, Business Information Technology or related field and 4+ years of experience working with data systems or tools in a business setting OR equivalent experience.

Nice To Haves

MS or PhD in Computer Science, Statistics, or a related quantitative field.
Experience with GenAI technologies and frameworks (e.g., LangChain, LlamaIndex, LLM APIs).
Experience with MLOps principles and tools (e.g., MLflow, Kubeflow, SageMaker, Vertex AI) for model versioning, deployment, and monitoring.
Experience with modern data stack and automation tools (e.g., Airflow, Databricks, dbt).
Deep understanding of GTM financial and operational metrics (e.g., pipeline, ACV, margin, LTV, CAC, Customer Health).
A self-directed, intellectually curious mindset with a proven ability to lead ambiguous, complex technical projects from 0 to 1.
A passion for AI coupled with a strong, opinionated perspective on how to strategically apply machine learning to drive business decisions in a fast-moving environment.
A resilient and resourceful "get-it-done" attitude, with the ability to thrive in a dynamic, fast-paced setting.
Proven ability to influence a technical roadmap and lead projects in a fast-moving, ambiguous environment.

Responsibilities

Design and deliver enterprise-grade data and analytics products, driving critical business decisions and championing visualization best practices.
Collaborate closely with data modeling teams to optimize performance and ensure scalable solutions.
Define and execute a strategic product vision, balancing business needs with technical constraints, and managing all stages of the product lifecycle.
Develop scalable data products and AI/ML models, integrating modern AI techniques to solve business problems.
Mentor a team of data scientists and engineers, setting high standards for technical rigor and code quality.
Translate complex technical concepts into actionable narratives for senior leadership and foster cross-functional collaboration.
Lead high-impact global data initiatives, architecting business-critical datasets and driving organizational success through data solutions.
Champion the adoption of data products across the organization, enabling teams to self-serve insights and make informed decisions.