> Markdown version of [/jobs/ext/2007639-data-scientist-infrastructure](https://www.wearedevelopers.com/jobs/ext/2007639-data-scientist-infrastructure). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist, Infrastructure - **Company:** Pinterest - **Location:** Circle, AK, United States (Remote available) - **Experience:** Expert - **Salary:** $140,000.0 - $288,000.0 - **Contract:** Permanent contract - **Skills:** Big Data, Computer Programming, Reliability Engineering, Standard Sql, Information Technology, Data Pipelines - **Published:** August 9, 2026 - **Apply:** https://www.workingnomads.com/job/go/1779414/ ## About the Role * 4+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems with large-scale data. * Bachelor's/Master's degree in a relevant field such as Computer Science, or equivalent experience." * Strong SQL and analytical programming skills, with experience working through messy, imperfect data and building reliable metrics and datasets. * Experience partnering on or contributing to production-ready data pipelines, measurement systems, or foundational data work that improves data quality and usability. * Solid foundation in experimentation and measurement, with the ability to design analyses, interpret results rigorously, and partner effectively with engineers and other cross-functional stakeholders. * Demonstrated ability to translate ambiguous problems into clear analytical workstreams and actionable recommendations. * Strong cross-functional communication skills, with the ability to explain technical findings clearly to engineering, product, and platform stakeholders. * Ability to operate independently, prioritize across both longer-term projects and fast-turn inbound requests, and drive work forward in a dynamic environment. * Curiosity and a builder mindset, with excitement for improving messy systems and creating more scalable, trustworthy measurement foundations. ## Description In this role, you will partner closely with engineering and cross-functional teams to improve how Pinterest measures, understands, and optimizes its infrastructure: * Partner with engineering teams to define, measure, and improve the health, quality, and efficiency of Pinterest's infrastructure systems. * Build and refine metrics, dashboards, and analytical frameworks that make complex technical systems more understandable and actionable. * Strengthen data foundations by improving metric definitions, auditing data quality, and contributing to pipeline and measurement improvements where needed. * Design and analyze experiments, investigations, and deep dives to quantify the impact of infrastructure changes on user experience, reliability, and business outcomes. * Translate ambiguous technical problems into clear analyses and actionable recommendations for engineering and platform partners. * Support high-priority investigations and decision-making related to infrastructure performance, reliability, cost, and measurement quality. * Identify opportunities to improve how Pinterest measures and optimizes infrastructure across a range of domains, such as performance, shopping infrastructure, governance, metrics quality, and site reliability., * We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role. * This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country. ## Related Videos - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [How building an industry DBMS differs from building a research one](https://www.wearedevelopers.com/videos/768-how-building-an-industry-dbms-differs-from-building-a-research-one) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Implementing continuous delivery in a data processing pipeline](https://www.wearedevelopers.com/videos/73-implementing-continuous-delivery-in-a-data-processing-pipeline) ## Related Articles - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Dev Digest 129 - Now that's what I call private data!](https://www.wearedevelopers.com/magazine/468-dev-digest-129-now-that-s-what-i-call-private-data) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)