Data Scientist II, Infrastructure Analytics

Promptcube3; Northern (KY); Remote; USD 114,000 - 235,000; Full time

Benefits offered by this job

Equity

Job summary

Pinterest is seeking a Data Scientist II to join the Infrastructure Data Science team in a remote, full-time capacity. You will collaborate with engineering and product teams to build measurable data foundations, metrics, and analytical frameworks that improve reliability, performance, and costs across core systems.

The role emphasizes experimentation, data quality, and the ability to translate complex technical problems into actionable insights, with a focus on scalable measurement foundations

Qualifications

• Master's degree in Statistics, Applied Math, Biostatistics or equivalent experience.
• Strong SQL and analytical programming skills; experience with messy data and building reliable metrics.
• Experience contributing to production-ready data pipelines and improving data quality.
• Solid grounding in experimentation and measurement; ability to design analyses and interpret results.
• Ability to translate ambiguous problems into clear analytical workstreams and actionable recommendations.

Responsibilities

• Partner with engineering and cross-functional teams to define, measure, and improve infrastructure health and efficiency.
• Build and refine metrics, dashboards, and analytical frameworks for complex systems.
• Design experiments and deep dives to quantify the impact of infrastructure changes on reliability, cost, and user experience.
• Communicate findings clearly to engineers, product, and platform stakeholders.
• Operate independently and prioritize long-term projects with fast-turn requests.

Skills

SQL

Analytical programming

Experiment design

Cross-functional communication

Education

Master's degree in Statistics / Applied Math / Biostatistics

Tools

Python

Job description

Pinterest is seeking a Data Scientist II to join the Infrastructure Data Science team in a remote, full-time capacity. You will collaborate with engineering and product teams to build measurable data foundations, metrics, and analytical frameworks that improve reliability, performance, and costs across core systems.

The role emphasizes experimentation, data quality, and the ability to translate complex technical problems into actionable insights, with a focus on scalable measurement foundations