Product Analytics Intern: Data Scientist (High Impact)

Meta; Menlo Park (CA); On-site; USD 80,000 - 135,000; Full time

Benefits offered by this job

Benefits

Job summary

Meta is seeking a Data Scientist Intern in Product Analytics for Summer 2027 in Menlo Park, CA. You will analyze large datasets to uncover actionable business insights and collaborate with a PM and engineers to shape product direction and governance.

You’ll work with SQL, Python, and R to build models and communicate results to cross-functional partners, helping identify opportunities and drive data-driven decisions across our product ecosystem.

Qualifications

• Currently pursuing a Bachelor’s and/or Master’s degree in Mathematics, Statistics, a relevant technical field, or equivalent practical experience.
• Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.

Responsibilities

• Perform large-scale data analysis to extract useful business insights.
• Identify actionable insights, suggest recommendations and influence the direction of the business by communicating results to cross-functional groups.
• Work closely with a Product Manager and Engineering team to proactively create rules and manage decisions.
• Classify leads so that the teams work on the most valuable cases.
• Suggest improvements in the tools and techniques to help scale the team and/or build 0->1 convictions on new initiatives. Model solutions around what delivers long-run user value to our users

Skills

SQL

Python

R

Education

Bachelor’s/Master’s degree in Mathematics/Statistics or related field

Job description

Meta is seeking a Data Scientist Intern in Product Analytics for Summer 2027 in Menlo Park, CA. You will analyze large datasets to uncover actionable business insights and collaborate with a PM and engineers to shape product direction and governance.

You’ll work with SQL, Python, and R to build models and communicate results to cross-functional partners, helping identify opportunities and drive data-driven decisions across our product ecosystem.