Job Description
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’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed.
At LinkedIn, we trust each other to do our best work where it works best for us and our teams. This role offers both hybrid (from Bay Area, New York City, Seattle/Bellevue) or remote work options, meaning you can work from home and commute to a LinkedIn office, depending on what’s best for you and when it is important for your team to be together, or this role can be performed remotely in most locations in the country of employment.
LinkedIn’s Jobs Marketplace is a complex ecosystem that requires a thorough understanding of demand and supply dynamics. With our recent investments in Agents and Language Models (LLMs) and improvements in our auction design, our product landscape and success metrics are changing significantly.
We need a technical and strategic tech lead to achieve the following goals:
- Enhance system understanding and operational excellence through AI explainability and interpretability.
- Boost job seeker engagement and revenue by identifying gaps and opportunities in our AI system.
- Improve AI systems and business metrics that align with customer, seeker, and LinkedIn value.
- Gain a deeper understanding of competitor pricing and ROI to inform both R&D and go-to-market strategies.
Responsibilities
Partner with cross-functional teams to initiate, lead and drive to completion large-scale/complex strategic projects for teams, departments and the company via data driven solutions
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.
Work with a team of high-performing data science professionals, and cross-functional teams to identify business opportunities, optimize product performance or strategy
Analyze large-scale structured and unstructured data; develop deep-dive analysis 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
Design and analyze experiments to test new product ideas or go to market strategies. Convert the results into actionable recommendations. Independently craft compelling stories; make logical recommendations; drive informed actions.
Engage with technology partners to build, prototype and validate scalable tools/applications end to end (backend, frontend, data) for converting data to insights.
Provide technical guidance and mentorship to junior team members on solution design as well as lead code/design reviews
Drive org-wide impact by shaping product and business strategy through data-centric storytelling and presentations
Act as a champion for a data-driven culture, evangelizing best practices both with LinkedIn and among the local and global data science community.
Basic Qualifications
- B.S. Degree in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc.
- 5+ years experience with SQL or relational database query performance, and at least one programming language (e.g., R, Python, Scala)
- 2+ years experience in an architect or technical leadership position
Preferred Qualifications
- 10+ years of overall experience with at least 5+ of those years leading teams technically
- Experience influencing strategy through data-centric presentations
- Experience in applied statistics and statistical modeling in at least one statistical software package
- Experience telling stories with data and visualization tools
- Experience running platform experiments and techniques like A/B testing
- Ability to work with multiple stakeholders, understand the product priorities, think with the big picture and solve core problems in the most efficient way
- Experience with manipulating massive-scale structured and unstructured data
- Proven record writing and optimizing code with high levels of craftsmanship, and coaching others to improve technical outputs
- •Experience mentoring other data scientists in an official or unofficial capacity
- Excellent communication skills, with the ability to synthesize, simplify and explain complex problems to different types of audience, including executives and compile compelling narratives
- Demonstrated thought leadership; experience publishing publicly visible research papers and/or speaking at conferences.
MS or PhD in a quantitative discipline: Statistics, Economics, Applied Mathematics, Operations Research, Computer Science, Informatics, Engineering, etc.
Suggested Skills:
- Data Science
- Experimentation
- Causal Inference
- Scala
- Python
LinkedIn is committed to fair and equitable compensation practices.
The pay range for this role is $162,000 to $267,000. 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
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.
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As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link:
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Job Tags
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