Meta
Research Scientist Intern, Central Applied Science (PhD)
Menlo Park, CA +1 · Internship · Posted Oct 22, 2026
- Location
- Menlo Park, CA
New York, NY - Experience
- 1+ years in programming, analysis, and visualization; research experience in at least one listed domain. Must be available for at least 16 weeks; internships are 12–24 weeks.
- Education
- Currently has, or is in the process of obtaining, a PhD in a quantitative field such as Statistics, Computer Science, Information Science, Economics, Operations Research, Data Science, Quantitative Marketing, or a relevant technical field.
- Visa sponsorship
- Must obtain work authorization in the country of employment by the time of hire and maintain it throughout employment.
About the job
Conduct research and develop scalable statistical and machine-learning solutions for Meta’s strategic decisions and products, collaborating with product teams and academic researchers.
What you'll do
- Develop rigorous, scalable methods for inference and decision-making using Meta’s data infrastructure.
- Partner across teams and communicate statistical best practices.
- Identify opportunities for data-scientific contributions and deliver research with practical impact.
What they ask for
- Currently pursuing or already holds a PhD in a quantitative or relevant technical field.
- Machine-learning and statistical research experience in at least one listed domain: statistical modeling, behavioral modeling, economics, model evaluation, or generative AI.
- 1+ years of programming, analysis, and visualization using software and libraries such as Python or R.
- Experience assembling or wrangling scalable datasets, such as with Hive, Spark, or Presto.
Nice to have
- A record of significant results through internships, industry experience, fellowships, patents, or first-authored publications at leading workshops or conferences.
- Cross-functional, cross-group, and cross-culture collaboration experience.
Pay
$7,650/month to $12,667/month (base salary)
Tools
Python, R, Hive, Spark, Presto
AI focus
Research and development involving generative AI and model evaluation, alongside statistical and machine-learning methods.
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