Company Description
LinkedIn is the worlds largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed.
Job Description
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
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
Qualifications
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 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
As part of the application process for this role, after an initial qualifications review, candidates are required to successfully complete the HackerRank online code challenge. Instructions for completion of the code challenge will be sent to you if your application is selected to move forward in the process. LinkedIn is committed to fair and equitable compensation practices.
The pay range for this role is $62 to $75. 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.
Additional Information
Equal Opportunity Statement
We seek candidates with a wide range of perspectives and backgrounds and we are 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 committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.
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.
San Francisco Fair Chance Ordinance
Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.
Pay Transparency Policy Statement
As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency.
Global Data Privacy Notice for Job Candidates
Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal.
