Associate, Decision Science

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.

The AI team within Tech COE organization is responsible for building the ultimate go-to-market engine to connect our solutions with customer needs at scale. As an Associate Decision Science, you will be partnering with stakeholders to crack the most important challenges to drive operational excellence and ultimately increase customer value.  

This role focuses on building and deploying AI and GenAI solutions that turn complex data into actionable business insights, improve forecasting, and drive operational efficiency. It involves solving advanced analytical problems, creating intelligent systems for sales teams, and partnering cross-functionally to scale data-driven processes and innovation. 

The ideal candidate should have a strategic mindset and strong communications skills to collaborate with cross-functional stakeholders and drive critical business decisions. The candidate should also be able to handle highly sensitive, confidential, and non-routine information, have high attention to detail, be open-minded to challenge the status quo and work in a rapidly changing organization in close collaboration with business partners. 

Responsibilities: 

• Deliver data-driven recommendations and insights to support strategic projects across GTMOps 
• Understand the business, track operational performance, provide insights and recommendations.  
• Manage expectations from stakeholders; manages deadlines/timeframes for larger initiatives and projects with minimal guidance on prioritization or dependencies. 
• Deploy the models in production systems & monitor/troubleshoot/debug production issues related to models. 
• Design, develop, test and deploy ML models and agents. 
• Collaborate closely with partner teams in infrastructure and AI to integrate with other systems to run a seamless ML pipeline. 
• Translate unstructured, complex business problems into scalable solutions.