Senior Behavioral Scientist

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.

LinkedIns 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 LinkedIns Global Business Organization (GBO). This is a unique opportunity to lead rigorous interpretable behavioral measurementconnecting what sellers do (in conversations workflows and coaching moments) to outcomes like pipeline progression win rate cycle time and renewal/upsell.

Youll 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. Youll 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 youre excited by applied research at scaleand want your work to shape how teams coach enable and prioritize investmentwed 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 arent 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 behavioroutcome 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 notpaired 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 $126000 to $204000. 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: Information :

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No

Employment Type :

Full-time