Tech Manager- GTM Applied AI & Analytics

This role is based in the Bangalore office.

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 Technology & Product Operations organization you will drive high-impact initiatives that strengthen our product and GTM operating systemleveraging proprietary data to improve product quality enable smarter tooling and reduce friction across member customer and GTM experiences.

We are seeking a talented and driven technical leader who excels at delivering world-class AI-powered analytic and agentic 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 business and technical acumen product judgment and are 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 operations and analytics colleagues on AI tooling and applications.

You will own complex initiatives from prototyping AI-driven concepts to deploying scalable automated systems. You will partner with R&D to build applications leveraging our internal platforms as well as provide input to R&D on enhancements to our technical platforms and data infrastructure. 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.

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 Technology & Product Operations org including key decisions on frameworks tooling and practices. Partner with R&D to build applications leveraging our internal platforms as well as provide input to R&D on enhancements to our technical platforms and data infrastructure

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 Operations Data Science and Engineering teams.

Technical Mentorship

• Mentor operations and analytics colleagues on AI tooling and applications 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

• 8 years of experience in data science machine learning or analytics engineering.
• 5 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).
• 1 years of experience with GenAI technologies and frameworks (e.g. LangChain LLM APIs).
• 1 years of architecting building and deploying machine learning models and/or automated data solutions in production environments.
• Bachelors 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

Additional Information :

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No

Employment Type :

Full-time