Company 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.
Join us to transform the way the world works.
Job Description
This role can be based in either our Sunnyvale, San Francisco, Bellevue, New York, Chicago, Atlanta, Omaha, or Washington D.C. offices.
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.
LinkedIn’s Go-To-Market Enablement (GTME) organization is on a mission to deliver data-driven insights and AI-powered tools that help our global sales teams excel. We are seeking a Senior Behavioral Scientist to join our Insights & Analytics team supporting LinkedIn’s Global Business Organization (GBO). This is a unique opportunity to lead rigorous, interpretable behavioral measurement—connecting what sellers do (in conversations, workflows, and coaching moments) to outcomes like pipeline progression, win rate, cycle time, and renewal/upsell.
You’ll apply your expertise in quantitative social science to define high-quality behavioral constructs, build defensible models, and translate findings into practical enablement and coaching decisions. You’ll collaborate with cross-functional partners across GTME and the business (e.g., Sales Performance Consultants, Sales Operations, and Engineering) to turn business questions into clear measurement plans and decision-ready insights. If you’re excited by applied research at scale—and want your work to shape how teams coach, enable, and prioritize investment—we’d love to have you help raise the standard for enablement impact at LinkedIn.
Responsibilities
- Discover emerging seller behaviors: Mine unstructured data (e.g., call transcripts) to identify novel, high-impact behaviors that distinguish top performers but aren’t yet captured in existing frameworks.
- Define behavioral measures that hold up under scrutiny: Translate high-volume behavioral signals (e.g., conversation behaviors, workflow signals, coaching interactions) into stable, interpretable constructs with clear definitions and documentation.
- Estimate behavior–outcome relationships with decision-grade rigor: Use appropriate longitudinal and hierarchical approaches, thoughtful controls, and clear assumptions to separate signal from noise and avoid common observational pitfalls.
- Evaluate enablement impact credibly: Design measurement strategies for programs and interventions, using experiments when feasible and quasi-experimental approaches when not—paired with robustness checks and sensitivity thinking.
- Communicate uncertainty clearly: Translate results into plain-English takeaways that include effect sizes, confidence/uncertainty, and the practical implications for coaching and enablement decisions.
- Set shared “claims standards” for Enablement: Establish reusable templates, analysis checklists, and guardrails.
- Multiply impact through mentorship: Coach the team and partners on causal inference methods, interpretation, and study design to raise the collective technical bar.
Qualifications
Basic Qualifications
- MS or PhD in a quantitative field (e.g., economics, statistics, psychometrics, political science, marketing science), or equivalent practical experience
- 5+ years of applied quantitative experience, including work with observational/longitudinal data; doctoral research can count toward experience.
- Experience with causal inference
- Experience communicating with non-technical stakeholders
- Experience in SQL and Python for data extraction and analysis.
Preferred Qualifications
- Strong preference for experience in marketing/media analytics (e.g., campaign measurement, funnel performance, demand gen), particularly in B2B contexts.
- Experience analyzing sales performance or commercial outcomes (pipeline, stage conversion, renewals/upsell, cycle time).
- Familiarity with conversation / call behavior data and translating it into reliable constructs and actionable coaching insights.
- Hands-on experience with causal inference methods (e.g., DoubleML, DiD, matching, event studies, sensitivity analyses) and/or experimentation design.
Suggested Skills
- Causal Inference
- Behavioral Measurement
- Technical Communication
LinkedIn is committed to fair and equitable compensation practices.
The pay range for this role is $126,000 to $204,000. Actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications, and specific office location. This may differ in other locations due to cost of labor considerations.
The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For additional 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.
