LinkedIn-posted 4 days ago
$62 - $75/Yr
Intern
Hybrid • Mountain View, CA

This internship role will be based out of Headquarters in Mountain View, California. 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. We are seeking data science interns to work on our rich datasets, encompassing text, graphs, and user interactions. Join us to tackle real-world problems through cutting-edge applied research, focusing on experimentation, causal inference, and machine learning. You will have the opportunity to build models to advance our understanding of ecosystem, develop insights through data mining and analytics, and apply advanced algorithms to improve measurement and recommendations. This role is ideal for those with a passion for translating data into impactful solutions and building scalable, data-driven insights and systems. Candidates must be currently enrolled in a PhD program, with an expected graduation date of December 2026 or later. Our internships are 12 weeks in length and will have the option of two intern sessions May 26th, 2026 - August 14th, 2026 June 15th, 2026 - September 4th, 2026

  • Analyze large-scale structured and unstructured data to gain actionable insights, identify patterns, and interpret user behaviors.
  • Conduct in-depth and rigorous causal analysis and develop causal methodology and machine learning models to drive member value
  • Explore vast datasets to discover relevant features and attributes that can improve the performance of existing models.
  • Extract valuable information from unstructured data sources and apply feature engineering techniques to enhance model effectiveness.
  • Continuously optimize and fine-tune models to meet business objectives and user expectations.
  • Initiate and drive projects to completion independently with production quality code and thorough documentation
  • Currently pursuing a PhD in computer science, statistics, mathematics, machine learning, or related technical field and returning to the program after the completion of the internship
  • Research experience related to one of the following domains: Experimentation and causal inference, Machine Learning, Differential Privacy, Forecasting, Econometrics, Operations Research, or related area, with publications in conferences.
  • Hands-on experience with machine learning, data mining, or statistics
  • Understanding of common programming languages used in Data Science , such as Python, Java, C++, and R
  • Experience with SQL/Relational databases
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