LinkedIn is the world’s largest professional network, built to help members of all backgrounds and experiences achieve more in their careers. Our vision is to create economic opportunity for every member of the global workforce. Every day our members use our products to make connections, discover opportunities, build skills and gain insights. We believe amazing things happen when we work together in an environment where everyone feels a true sense of belonging, and that what matters most in a candidate is having the skills needed to succeed. It inspires us to invest in our talent and support career growth. Join us to challenge yourself with work that matters. 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 1 billion 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 seeking a talented and driven individual to accelerate our efforts and contribute to LinkedIn’s data-centric culture. In this role, you will tackle a wide range of technical challenges spanning products, engineering, research, data engineering, finance, and infrastructure. Leveraging data and analysis, you will address critical challenges within our infrastructure organization, shaping product strategy and guiding investment decisions with data-driven insights. LinkedIn’s infrastructure is the backbone of our operations, encompassing datacenters, servers, network infrastructure, power systems, and foundational software platforms that power our products and services. Responsibilities • Work with a team of high-performing analytics, data science professionals, and cross-functional teams to identify business opportunities and develop algorithms and methodologies to address them. • Analyze large-scale structured and unstructured data. • Develop methodologies to enhance LinkedIn’s operations and platform capabilities. • Apply technical expertise to our forecasting and capacity planning process to seek opportunities of improvement • Engage with technology partners to build, prototype and validate scalable tools/applications end to end (backend, frontend, data) for converting data to insights. • Promote and enable adoption of technical advances in Data Science; elevate the art of Data Science practice at LinkedIn. • Improve LinkedIn’s ability to measure and credibly speak to labor market trends and other economic phenomena. • Initiate and drive projects to completion independently. • Act as a thought partner to senior leaders to prioritize/scope projects, provide recommendations and evangelize data-driven business decisions in support of strategic goals. • Partner with cross-functional teams to initiate, lead or contribute to large-scale/complex strategic projects for team, department, and company. • Provide technical guidance and mentorship to junior team members on solution design as well as lead code/design reviews. Basic Qualifications: • Bachelor’s Degree in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc. • 5+ years of industry or relevant academia experience • Background in at least one programming language (eg. R, Python, Java, Ruby, Scala/Spark or Perl) • Experience in applied statistics and statistical modeling in at least one statistical software package, (eg. R, Python) Preferred Qualifications: • 7+ years of industry or relevant academia experience • MS or PhD in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc. or other quantitative field. • Experience in infrastructure planning, operations research, or a related field • Familiarity with cloud computing platforms and infrastructure management systems. Suggested Skills • Statistical Modeling • Forecasting • Programming • Data Analysis • Infrastructure Planning You will Benefit from our Culture: We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $164,000 - $268,000. 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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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. 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