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. The Trust Data Science team delivers insights, metrics, and data solutions as part of the cross-functional Trust team to realize its mission to create safe, trusted, professional experiences where individuals and organizations can be productive and successful. Nested within Trust DS, the Applied Science team solves some of the complex problems of measurement and experimentation with research and cutting edge technologies. As the manager of this team, you lead and grow a world-class group of applied scientists and statisticians, fostering a culture where scientific rigor meets product velocity. 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 data science professionals, and cross-functional partners (product, engineering, AI, policy, and operations) to build high fidelity abuse prevalence and false positive metrics using advanced algorithms and models Build and operate advanced experimentation methodologies (holdouts, network / adversary aware testing frameworks, variance reduction) so product and AI/Eng teams can measure impact quickly and rigorously Deploy approaches like ML assisted sampling, anomaly detection, and automated root-cause analysis to drive agility in identifying and mitigating emerging abuse patterns Work with the team and cross-functional partner to identify business opportunities and develop inference, algorithms, models and experimentation methodologies to address them Lead the team to conduct in-depth and rigorous causal analysis and develop causal methodology and machine learning models to drive member value Guide the team to 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. Promote and enable adoption of technical advances in Data Science; elevate the art of Data Science practice at LinkedIn 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. 1+ years of management experience or 1+ years of staff level engineering experience with management training 5+ years of relevant work experience Background in at least one programming language (eg. R, Python, Java, Scala/Spark) Experience in applied statistics and statistical modeling in at least one statistical software package, (eg. R, Python) Preferred Qualifications: Master’s degree or PhD in quantitative fields, such as Economics, Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics. 2+ years of hands-on software engineering/technical management and people management experience 7+ years industry experience in software design, development, and algorithm related solutions. Research experience related to one of the following domains: Experimentation and Causal inference, Machine Learning, Econometrics, Operations Research, or related area, with publications in conferences 3+ years experience working in Trust & Safety domain, particularly in adversarial abuse Suggested Skills: Machine Learning Experimentation Causal Inference 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 $164,000.00 to $268,000.00 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 Equal Opportunity Statement We 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. 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:
...Call Center Assistant Manager Infosys McCamish Des Moines, IA The Operations Assistant Manager role is an integral member of... ...years as a virtual insurance company. Infosys McCamish has expert technology and outsourcing credentials, along with a proven business...
...prepare students for success in education, the workforce and the community through a school that integrates literacy, standards-based academics and culturally responsive supportive services. WHAT WE ASK OF OUR TEACHERS Teach Drive student mastery of core and...
...Tech is looking for a Visual Media Content Creator to capture our capabilities and services for both internal training and external marketing uses. This position is based out of our headquarters in Antioch, California, and includes occasional travel to project sites at...
...Executive Advisors are the most experienced advisors in the firm. They have two primary job functions: work with top 20% of the most profitable and/or complicated clients in the firm and the remaining 80% developing new client relationships. They also spend a significant...
...Desired Qualifications: Associate's degree or equivalent experience in a S.T.E.M related field Previous experience testing medical device in regulated FDA/QSR and ISO environments. Hands on experience and interest with mechanical aptitudes Pay and Benefits...