Associate, Decision Science

Job Description

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. 

Qualifications

Basic Qualifications: 

• Masters or PHD in Computer Science or related technical discipline. 
• 4+ years of experience in Python, R or Scala. 
• 4+ years of experience with machine learning, personalization algorithms, privacy enhancing technologies (PETs), optimization algorithms, and/or deep-learning techniques. 
• 3+ years of experience with building AI models and multi product deployment.  

Preferred Qualifications:  

• Experience in deploying machine learning models in Azure cloud. 
• Experience with distributed data systems such as Hadoop and related technologies (Spark, Presto, Pig, Hive, etc.) 
• Background in any one of programming language (C#, Java, PHP, JavaScript) 
• Experience in integrating AI solutions with different systems and software. 
• Strong fundamentals in Statistics and Optimization. 
• Exposure to Deep Learning and Reinforcement Learning is a plus. 
• Experience applying quantitative analysis to solve business problems and making data-driven business decisions 
• Experience effectively communicating complex concepts through written and verbal communication 
• Deep understanding of technical and functional designs for relational and MPP Databases. 
• Experience in data visualization and dashboard design 
• Published work in academic conferences or industry circles 

Suggested skills

• Machine Learning & Deep Learning
• AI Model Deployment
• Distributed Data Systems

Additional Information

India Disability Policy 

LinkedIn is an equal employment opportunity employer offering opportunities to all job seekers, including individuals with disabilities. For more information on our equal opportunity policy, please visit https://legal.linkedin.com/content/dam/legal/Policy_India_EqualOppPWD_9-12-2023.pdf

Global Data Privacy Notice and Compliance Posters for Job Candidates 

Please use this link to access documents that provide information about how LinkedIn handles the personal data of employees and job applicants, as well as the E-Verify Participation Notice and the Department of Justice Immigrant and Employee Rights Section Right to Work posters: https://www.linkedin.com/legal/candidate-portal.