Senior Applied Scientist: ML, Causal Inference & Personalization

LinkedIn; Mountain View (CA); Hybrid; USD 144,000 - 236,000; Full time

Job summary

LinkedIn is seeking a Data Scientist to join the Data Science and Applied Science teams in Mountain View, CA. The role focuses on experimentation, causal inference, and large-scale machine learning to solve product and business problems.

You will build methods and models and translate ideas into scalable tools that impact member experience and monetization. The ideal candidate blends deep technical skill with strong product judgment, collaborating with Engineering, AI, and Product to deliver

Qualifications

• Bachelor's degree in a quantitative field (stats, OR, CS, econ) required.
• 3+ years of industry or academia experience in a relevant area.
• Experience in at least one programming language (R, Python, Java, Ruby, Scala/Spark or Perl).
• Experience in applied statistics and statistical modeling using R or Python.

Responsibilities

• Support product and data solution improvements through structured analysis.
• Run experiments, analyses, and modeling to evaluate product impact.
• Collaborate with cross-functional teams to define analytical tasks.
• Develop and refine ML models or statistical approaches for product needs.
• Ensure rigor and reproducibility in analyses and modeling work.
• Communicate findings and recommendations to stakeholders.
• Review methodologies and tools to improve scientific rigor.
• Translate business goals into analytical tasks for ML models.

Skills

Machine Learning

Statistics

Programming Languages

Education

Bachelor's degree in quantitative field

Doctorate in statistics / related field

Tools

R

Python

Java

Ruby

Scala/Spark

Perl

Job description

LinkedIn is seeking a Data Scientist to join the Data Science and Applied Science teams in Mountain View, CA. The role focuses on experimentation, causal inference, and large-scale machine learning to solve product and business problems.

You will build methods and models and translate ideas into scalable tools that impact member experience and monetization. The ideal candidate blends deep technical skill with strong product judgment, collaborating with Engineering, AI, and Product to deliver