Staff Applied Scientist

LinkedIn is the world's 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. We are also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture built on trust, care, inclusion, and fun where everyone can succeed. Join us to transform the way the world works.Job DescriptionLinkedIn's Data Science team leverages big data to empower business decisions and deliver data‐driven insights, metrics, and tools to drive member engagement, business growth, and monetization efforts. With over 1 billion members worldwide and a focus on great user experience across B2B and B2C programs, a career at LinkedIn offers countless opportunities for an ambitious data scientist to have an impact.We are looking for a talented and driven individual to accelerate our efforts and play a major part in our data‐centric culture. The role requires strong experimentation and/or machine learning skills, the ability to implement techniques from scratch, and the business savvy to turn technical solutions into better business decisions.Work will be hybrid: both home and a LinkedIn office on select business‐needed days.ResponsibilitiesWork with 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.Conduct rigorous causal analysis and develop causal methodology and machine learning models to drive member value and customer success.Develop methodologies to enhance LinkedIn's product and platform capabilities.Engage with technology partners to build, prototype, and validate scalable tools/applications end‐to‐end—including backend, frontend, and data—for converting data to insights.Promote and enable adoption of technical advances in Data Science; elevate the practice at LinkedIn.Improve LinkedIn's ability to measure labor market trends and other economic phenomena.Initiate and drive projects to completion independently.Act as a thought partner to senior leaders, prioritizing scopes, providing recommendations, and evangelizing data‐driven decisions to support strategic goals.Partner with cross‐functional teams to initiate, lead, or contribute to large‐scale strategic projects.Provide technical guidance and mentorship to junior team members on solution design and lead code/design reviews.QualificationsBasic QualificationsBachelor's Degree in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc.5+ years of industry or relevant academic experience.Background in at least one programming language (e.g., R, Python, Java, Ruby, Scala/Spark, or Perl).Experience in applied statistics and statistical modeling in at least one statistical software package (e.g., R, Python).Preferred Qualifications7+ years of industry or relevant academic experience.MS or PhD in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc.Suggested SkillsMachine LearningResearchCausal InferenceYou Will Benefit From Our CultureWe strongly believe in the well‐being of our employees and their families, offering 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 $170,000 – $277,000. Actual compensation packages consider skill set, depth of experience, certifications, and specific work location. The total compensation may also include annual performance bonus, stock, benefits, and other incentive plans. For more information, visit LinkedIn benefits .Additional InformationEqual Opportunity StatementWe 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.If you need a reasonable accommodation to search, apply, or interview, contact accommodations@linkedin.com with the specific accommodation requested.Reasonable accommodations include but are not limited to:Documents in alternate formats or read aloud to you.Interviewing 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. Non‐disability requests (e.g., application follow‐up) will not receive a response.LinkedIn will not discharge or discriminate against employees or applicants who have inquired about or disclosed their own pay or the pay of another employee or applicant. Employees who have access to compensation information as part of their essential job functions cannot disclose pay without formal or investigative justification.San Francisco Fair Chance OrdinancePursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider qualified applicants with arrest and conviction records.LinkedIn follows the Pay Transparency and non‐discrimination provisions described at https://lnkd.in/paytransparency .Global Data Privacy Notice for Job CandidatesAccess the privacy notice at https://legal.linkedin.com/candidate-portal .#J-18808-Ljbffr