Sr. Tech Lead, GTM Applied AI & Analytics

This role is based in either our Sunnyvale San Francisco New York or Chicago offices. 

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.    

As part of the Product Operations organization you will leverage one of the richest proprietary datasets in the world to lead high-impact initiatives that deepen intelligence across our members and customers and elevate product quality.

We are seeking a talented and driven technical leader who excels at delivering world-class AI-powered analytic solutions actionable insights and measurable business impact. You will design and implement data-driven initiatives that create both immediate value and long-term strategic advantage.

You bring strong technical acumen product judgment and business savvy with applied expertise in modern AI tools and techniques. You combine analytical rigor with a growth mindset to generate scalable data-driven learnings. You are comfortable navigating large complex and ambiguous data ecosystems and influencing cross-functional stakeholders through strong relationship-building and collaboration.

This is a hands-on player-coach leadership role. You will architect solutions write production-grade code using AI tools and mentor a team of 34 data scientists and analytics engineers.

You will own the end-to-end technical lifecycle of complex initiatives from prototyping AI-driven concepts to deploying scalable automated systems. Combining the analytical depth of a principal data scientist with executive-level storytelling your primary goal is to architect and build agentic workflows predictive models and automated systems that fundamentally transform how operations teams operate.

Responsibilities

Architect & Build

• Lead the hands-on design development and deployment of scalable data products AI/ML models (e.g. member friction customer impact anomaly detection) and GenAI-powered agentic workflows.

Technical Strategy

• Define the technical roadmap and architecture for the Product Operations Applied AI pillar including key decisions on frameworks tooling and practices.

End-to-End Automation

• Write high-quality production-ready Python and SQL to build and maintain automated data pipelines advanced analytics and insight-delivery systems.

Applied AI Integration

• Serve as the subject matter expert on applying modern AI LLMs and ML techniques (e.g. RAG fine-tuning) to solve GTM business problems in partnership with Data Science and Engineering teams.

Technical Mentorship

• Mentor and develop a team of data analysts and engineers setting a high bar for technical rigor code quality and engineering best practices through a lead-by-example approach.

Executive Storytelling

• Translate complex technical concepts and model outputs into clear concise and actionable narratives for senior GTM and Operations leadership.

Cross-Functional Partnership

• Collaborate with Product Engineering and Data Science teams to operationalize and scale models from prototype to production ensuring reliability and measurable business impact.

Qualifications :

Basic Qualifications

• 7 years of experience in data science machine learning or analytics engineering.
• 7 years of experience in Python for data manipulation (pandas NumPy) analytics and ML (e.g. scikit-learn TensorFlow PyTorch).
• SQL experience with large-scale data warehouses (e.g. Presto Trino Spark SQL).
• 3 years of experience with GenAI technologies and frameworks (e.g. LangChain LLM APIs).
• 3 years of architecting building and deploying machine learning models and/or automated data solutions in production environments.
• BA/BS in Computer Science Statistics Operations Research Engineering or a related quantitative field (or equivalent practical experience).

Preferred Qualifications

• MS or PhD in Computer Science Statistics or a related quantitative field.
• Experience with modern data stack and automation tools (e.g. Airflow Databricks).
• Proven ability to lead ambiguous complex technical initiatives from 01.
• Demonstrated experience influencing technical roadmaps in fast-moving environments.
• Resilient resourceful and self-directed with a strong bias for action.
• Passion for AI with a clear strategic perspective on applying machine learning to drive business decisions.

Suggested Skills

• Python
• SQL
• Data Science
• Machine Learning
• Model Development & Deployment

LinkedIn is committed to fair and equitable compensation practices.

The pay range for this role is $150000 to $243000. Actual compensation is based on multiple factors including skills experience certifications and location. Compensation may vary in other locations due to cost-of-labor considerations.

Total compensation may include annual performance bonus stock benefits and other applicable incentive compensation plans. For additional information visit: Information :

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No

Employment Type :

Full-time