PhD Applied Science Intern- Data Science

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 documentationBasic 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 InferenceLinkedIn 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 StatementLinkedIn 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/EeE8sk7CTIdFmEp9ONzFOTEBM62TPrWLMHs4J1CQxVTbg?e=5hfhpE. Please reference https://www.eeoc.gov/sites/default/files/2023-06/22-088EEOCKnowYourRights6.12ScreenRdr.pdf and https://www.dol.gov/ofccp/regs/compliance/posters/pdf/OFCCPEEOSupplementFinalJRFQA508c.pdf for more information.LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. 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