Senior Data Scientist

LinkedIn • Sunnyvale, CA

4d • Hybrid

About The Position

LinkedIn's Data Science team uses member and customer behavior to inform product decisions across its professional network. The Senior Data Scientist will own ambiguous, high-impact problems end-to-end, using statistical intuition and data science methods to define metrics that guide product strategy, investigate marketplaces, and evaluate AI-native features. The role partners closely with product managers and engineers to translate findings into roadmap decisions and help build features that create economic opportunity for members.

This role is hybrid, performed both from home and from a LinkedIn office on select days based on team business needs. It involves experimentation, causal analysis, predictive modeling, AI/LLM system evaluation, and the development of data solutions. The Senior Data Scientist will communicate analytical findings to internal customers, support prioritization, and help embed data science best practices across solution development.

Requirements

• Bachelor's degree in a quantitative discipline such as Computer Science, Statistics, Operations Research, Informatics, Engineering, Applied Mathematics, or Economics.
• At least 3 years of relevant industry or academic experience working with large amounts of data.
• Experience influencing strategy through data-centric presentations.
• Experience with SQL.
• Background in at least one programming language, such as R, Python, or Scala.
• Experience in applied statistics and statistical modeling using at least one statistical software package.
• Experience communicating insights with data and visualization tools.
• Experience running platform experiments and techniques such as A/B testing.

Nice To Haves

• Master's degree or doctorate in Applied Mathematics, Computer Science, Data Science, Economics, Engineering, Informatics, Statistics, or a related field.
• Experience with SQL and Python.
• Experience with experimentation design and analysis, including variance reduction.
• Experience with causal inference methods.
• Product intuition for two-sided marketplaces.
• Clear written communication.
• Ability to understand how to measure AI-powered product experiences.

Responsibilities

• Design and perform data-driven experiments and causal analyses to test product ideas and go-to-market strategies, develop ecosystem understanding, and monitor products or systems.
• Evaluate A/B testing and causal analysis tools for gaps; potentially partner with Applied Sciences teams to create testing protocols and methods and analyze ramp performance.
• Leverage AI tools in day-to-day workflows to increase productivity.
• Partner with internal customers to translate business problems into data-verifiable hypotheses.
• Develop and employ models and causal analyses, such as panel analysis and A/B testing, to identify drivers of metric relationships and generate actionable insights in moderately complex product domains.
• Independently diagnose issues and identify opportunities to improve AI/LLM systems.
• Prototype data solutions and collaborate with partners such as Data Science and Engineering teams to operationalize, build, and validate scalable tools, applications, or solutions for internal customers.
• Apply data science best practices throughout the development of customized and scalable data solutions, and provide feedback to junior team members.
• Communicate with partners and internal customers to scope data-driven investigations and experiments, contributing recommendations about priorities.
• Develop and run predictive models to estimate the impact of initiatives on identified KPIs.
• Create compelling, data-centric stories from analytical findings to support internal customers' decision-making.

Benefits

• Health and wellness programs.
• Time away for employees.
• Annual performance bonus may be included in the total compensation package.
• Stock may be included in the total compensation package.
• Benefits and/or other applicable incentive compensation plans may be included in the total compensation package.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior