Company Description 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. Join us to transform the way the world works.

Job Description Applied Science teams at LinkedIn empower the company’s products and businesses by driving impact through methodological innovation at scale. We conduct research and build solutions to tackle some of the most challenging business problems across LinkedIn’s ecosystem—from market and system design (e.g., auctions, matching), to optimization and personalization. Composed of scientists passionate about translating theory into practice, these teams build scalable, production-ready solutions (e.g., models, tools and platforms) that support product, customer value, and long-term business growth.

As a Senior Applied Scientist, you will play a critical role in advancing LinkedIn’s next generation of AI-powered systems by leading methodological research in areas such as prediction, measurement, and optimization, and transforming research into scalable, production-grade models, tools and platforms. In this role, you will drive cutting-edge R&D and integrate advanced methodologies into end-to-end systems that operate across multiple LinkedIn products and surfaces. You will design and develop novel methods and models, and deploy large-scale ML / DL / RL / LLM solutions that are reliable, efficient, and maintainable in production. You will transform research solutions into robust, reusable tooling and platforms, and work on problems to boost the growth of LinkedIn's diverse products.

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

• Identify and shape new opportunities where advances in methodology, AI, or system design can unlock step-function improvements to marketplace performance and platform health.
• Lead methodological research in optimization or measurement, for large-scale, multi-sided marketplaces, including auction design, matching mechanisms, and personalization.

Qualifications Basic Qualifications

• Bachelor's Degree in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc.
• 3+ 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

• PhD or Master’s degree in a quantitative field such as Computer Science, Machine Learning, Statistics, Economics, Operations Research, or a related discipline, with a strong research foundation.
• MS and 3+ years of relevant work experience, or Ph.D. and 1+ years of relevant work experience developing and deploying machine learning or optimization systems in large-scale, production environments.
• Demonstrated experience applying advanced methodologies to real-world marketplace, recommendation, auction, pricing, advertising, or ranking systems or building scalable tooling or platform
• Publications in top-tier conferences or journals (e.g., NeurIPS, ICML, KDD, WWW) or equivalent industry research contributions are a plus.

Suggested Skills

• ML/AI System
• Statistical Modeling
• Platform/System Design
• Optimization Techniques (Bandits, RL, Multi-objective Optimization)
• LLM/transformer-based Models or Systems
• Research

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 $139,000.00 to $229,000.00 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.

Additional Information 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:

• 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.

San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.

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 Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal.