LinkedIn-posted 1 day ago
$50 - $60/Yr
Intern
Hybrid • Mountain View, CA

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. 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. LinkedIn’s Data Science team leverages big data to empower business decisions and deliver data-driven insights, metrics, and tools in order to drive member engagement, business growth, and monetization efforts. With over 500 million members around the world, a focus on great user experience, and a mix of B2B and B2C programs, a career at LinkedIn offers countless ways for an ambitious data scientist to have an impact. We are looking for talented and driven data science interns to accelerate our efforts and be a major part of our data-centric culture. This person will work closely with various cross-functional teams such as product, marketing, sales, engineering and operation to develop and deliver metrics, analyses, solutions, and insights, with actionable recommendations to business partners. Successful candidates will exhibit technical acumen and business savvy, with a passion for making an impact through creative storytelling and timely actions. Candidates must be currently enrolled in a Master's degree 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

  • Work with a team of high-performing data engineering professionals, and cross-functional teams to identify business opportunities and build scalable data solutions.
  • Build data expertise, act like an owner for the company and help manage complex data systems for a product or group of products.
  • Perform all of the necessary data transformations to serve products that empower data-driven decision making.
  • Establish efficient design and programming patterns for engineers as well as for non-technical partners.
  • Design, implement, integrate and document performant systems or components for data flows or applications that power analysis at a massive scale.
  • Understand the analytical objectives to make logical recommendations and drive informed actions.
  • Engage with internal data platform teams to prototype and validate tools developed in-house to derive insight from very large datasets or automate complex algorithms.
  • Currently pursuing a Master's Degree in a quantitative discipline: computer science, statistics, applied mathematics, operations research, management of information systems, engineering, economics or equivalent and returning to the program after the completion of the internship.
  • Experience in at least one programming language (eg. Python, R, Hive, Java, Ruby, Scala/Spark or Perl etc.).
  • Experience with SQL or other relational databases.
  • Experience in Hadoop or other MapReduce paradigms and associated languages such as Pig and Hive.
  • Experience or exposure in developing data pipelines using Spark and Hive.
  • Experience with data modeling, ETL (Extraction, Transformation & Load) concepts, and patterns for efficient data governance.
  • Experience working with databases that power APIs for front-end applications.
  • Understanding data visualization tools (eg. Tableau, BI dashboarding, R visualization packages, etc.).
  • Experience building front-end visualizations using JavaScript frameworks (eg. jQuery, Marionette, D3, or Highcharts).
  • Experience in applied statistics and statistical modeling in at least one statistical software package, (eg. Advance R package, SAS, SPSS).
  • Ability to communicate findings clearly to both technical and non-technical audiences.
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