LinkedIn was built to help professionals achieve more in their careers, and every day millions of people use our products to make connections, discover opportunities, and gain insights. Our global reach means we get to make a direct impact on the world’s workforce in ways no other company can. We’re much more than a digital resume – we transform lives through innovative products and technology.
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 2025 or later.
At LinkedIn, we trust each other to do our best work where it works best for us and our teams. This role offers a hybrid work option, meaning you can both work from home and commute to a LinkedIn office, depending on what’s best for you and when it is important for your team to be together. Our internship roles will be based in Mountain View, CA; or other US office locations.
Our internships are 12 weeks in length and will have the option of two intern sessions:
• May 27th, 2025 - August 15th, 2025
• June 16th, 2025 - September 5th, 2025
Responsibilities:
• 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
Basic Qualifications:
• 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 top tier conferences.
• Hands-on experience with machine learning, data mining, or statistics
Preferred Qualifications:
• Understanding of common programming languages used in Data Science , such as Python, Java, C++, and R
• Experience with SQL/Relational databases
Suggested Skills:
• Machine Learning
• Research
• Causal Inference
LinkedIn is committed to fair and equitable compensation practices.
The pay range for this role is $57- $70 per hour. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor.
The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits.
Equal Opportunity Statement
LinkedIn is committed to diversity in its workforce and is proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is an Affirmative Action and Equal Opportunity Employer as described in our equal opportunity statement here: https://microsoft.sharepoint.com/:b:/t/LinkedInGCI/EeE8sk7CTIdFmEp9ONzFOTEBM62TPrWLMHs4J1C_QxVTbg?e=5hfhpE. Please reference https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf and https://www.dol.gov/ofccp/regs/compliance/posters/pdf/OFCCP_EEO_Supplement_Final_JRF_QA_508c.pdf for more information.
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If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at accommodations@linkedin.com and describe the specific accommodation requested for a disability-related limitation.
Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:
-Documents in alternate formats or read aloud to you
-Having interviews in an accessible location
-Being accompanied by a service dog
-Having a sign language interpreter present for the interview
A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response.
LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.
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As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency.
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This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://lnkd.in/GlobalDataPrivacyNotice
