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. 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, LinkedIn offers countless ways for ambitious Data Scientists to have an impact and transform their careers. We are now looking for a talented and driven individual to accelerate our efforts and be a major part of our data-centric culture. As part of our Go-to-market Sales & Payments AI team, this person will work closely with various cross-functional teams such as product, marketing, sales, engineering, policy and operations to develop and deliver metrics, analyses, advanced machine learning / AI solutions, with actionable recommendations to business partners. Successful candidates will exhibit technical acumen, product sense and business savviness, with a passion for making an impact through continuous learning, their technical skills, creative storytelling and timely actions. 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. Responsibilities: • Work with a team of high-performing analytics, data science professionals, and cross-functional teams to identify business opportunities and develop strategies and ML/AI methodologies to address them. • Drive customer success by shaping product and business strategy for Go-to-market initiatives through data-centric presentations, in-depth and rigorous model development and improvement, A/B testing experiments, observational causal studies to quantify the cause and effect in the ecosystem. • Engage with technology partners to build, prototype and validate scalable tools/applications end to end (backend, frontend, data) for converting data to insights. • Analyze large-scale structured and unstructured data; develop deep-dive analyses and machine learning models to drive member value and customer success. • Design and develop core business metrics, create insightful automated dashboards and data visualization to track them and extract useful business and product insights. • Engage with technology partners to build, prototype and validate scalable tools/applications end to end (backend, frontend, data) for converting data to insights. • 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: Computer Science, Statistics, Operations Research, Informatics, Engineering, Applied Mathematics, Economics, etc. • 3+ years of relevant industry or relevant academia experience working with large amounts of data • Experience influencing strategy through data-centric presentations. • Experience in SQL. • Background in at least one programming language (e.g., R, Python, Scala). • Experience in applied statistics and statistical modeling in Python. • Experience telling stories with data and visualization tools. • Experience running platform experiments and techniques like A/B testing. Preferred Qualifications: • BS and 5+ years of relevant work experience, MS and 3+ years of relevant work experience, or Ph.D. and 1+ years of relevant work/academia experience working with large amounts of data • MS or PhD in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc. • Experience with manipulating massive-scale structured and unstructured data. • Working knowledge of Unix command-line/shell, git and review board. • Experience leveraging government data or publicly available third-party APIs. • Excellent communication skills, with the ability to synthesize, simplify and explain complex problems to different types of audience. Suggested Skills: • SQL, Python • Statistical Analysis • Data Storytelling • Machine Learning 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 $116,000.00 to $190,000.00. 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. 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. 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 This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://lnkd.in/GlobalDataPrivacyNotice