Operations Analytics & Insights, Tech Lead

About the Role

LinkedIn is seeking an Operations Analytics & Insights Tech Lead to support its Strategy, Planning & Operations organization. This role focuses on shaping operational analytics and performance measurement across Global Support and Product Operations. The position spans the full lifecycle of complex initiatives, from exploring new AI-led ideas to launching scalable automated solutions. You will work closely with business leaders, Strategic Finance, Product, Engineering, and Operations to uncover opportunities, define solutions, and deliver measurable outcomes.

The job is based in Bengaluru and follows LinkedIn’s hybrid work model, meaning you will split your time between home and a LinkedIn office depending on team and business needs.

About LinkedIn

LinkedIn is a professional network designed to expand economic opportunity for people across the global workforce. Its products help members build connections, find opportunities, develop skills, and gain insights that support their work and careers. The company also emphasizes employee growth and aims to foster a culture of trust, care, inclusion, and fun.

The broader mission is to help transform how the world works.

Key Responsibilities

• Create scalable data products and AI/ML models that address business challenges within LinkedIn’s Global Support function.
• Partner with upstream technical teams to move models from proof of concept into production and ensure they perform reliably at scale.
• Spot operating patterns, bottlenecks, and improvement areas that can increase efficiency, performance, and scalability.
• Turn highly technical findings and model outcomes into clear, practical recommendations for senior GTM and Operations leaders.
• Own analytical initiatives end to end and help build a strong analytics team capability.

Qualifications

• At least 8 years of experience using data systems or analytical tools in a business environment, or equivalent experience.
• Hands-on experience with SQL and large-scale data warehouses such as Presto, Trino, or Spark SQL.
• Background in designing, building, and deploying machine learning models and/or automated data solutions in production.
• A bachelor’s degree in a quantitative discipline such as Computer Science, Statistics, Operations Research, or Engineering, or equivalent practical experience.

Preferred Qualifications

• Exposure to developer or AI-assisted coding tools such as Claude Code or Cursor.
• Experience with modern data stack and workflow automation tools such as Airflow, Databricks, and dbt.
• Strong understanding of support-related financial and operational measures, including resolution time, SLA, and customer health.
• Self-driven, intellectually curious, and able to navigate ambiguous, complex technical work from concept to launch.
• Strong enthusiasm for AI and a thoughtful approach to applying AI tools to improve business decisions in a fast-moving environment.

Additional Information

LinkedIn provides equal employment opportunity and welcomes applicants with disabilities. The company also shares required privacy and compliance notices for candidates regarding personal data handling and work authorization documentation.