# Data Scientist II, Experimentation

**Company**: Pinterest
**Location**: San Francisco, CA, US; Remote, US
**Work arrangement**: remote
**Experience**: senior
**Job type**: full-time
**Salary**: $114,297-$235,319 USD
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/pinterest/jobs/7896291?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_7984daf2-b2c

## Description

We're seeking a data scientist with a strong background in experimentation and statistical analysis to help us improve and iterate on our experimentation platform. The successful candidate will play a key role in improving our experiment processes at scale, leveraging their expertise to drive innovation and help make sure that Pinterest users are receiving the most thoroughly data-driven features.

With thousands of experiments running concurrently, the magnitude of our operations presents a significant opportunity for impact. If you possess a strategic mindset, proven experience in experimental design and analysis, and a passion for driving results, we invite you to join us in shaping the future of experimentation.

Responsibilities:

- Comb through the literature in experimentation to identify potential methodologies that can improve parts of our platform where we have the biggest opportunities.

- Make the process of setting up, running and evaluating experiments smoother and more repeatable for our platform users, ensuring that decisions are risk-aware and consistent.

- Write workflows to make our vast experimentation meta-data able to be leveraged by our team and outside of our team to better understand the experimentation landscape.

- Consult with product data science teams to debug, design or improve their experiments and experimentation process.

Requirements:

- PhD in a relevant field (stats, applied math, biostatistics, etc…) OR 2+ years of hands-on experience working as a data scientist or applied scientist.

- Experience working directly on experimentation problems and an awareness of state of the art methodologies.

- The ability to write clean, efficient, and scalable code that can be easily maintained and extended by other team members.

- Proficiency in software development best practices, including version control systems such as Git, to ensure efficient collaboration, code management, and reproducibility in a data science environment.

- Familiarity with workflow management tools such as Apache Airflow to create and schedule data pipelines, allowing for automated and reliable execution of machine learning workflows.

## Skills

### Required
- PhD in stats, applied math, biostatistics, etc…
- Experimentation
- Statistical analysis
- Software development best practices
- Version control systems
- Apache Airflow

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/pinterest/jobs/7896291?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)