Decision Scientist II

ZipRecruiter•Santa Monica, CA

1d•$130,000 - $155,000•Hybrid

About The Position

As a Decision Scientist II, you will collaborate closely with product management, engineering, design, and marketing teams to drive the development, prioritization, and planning of the product roadmap. You will transform insights into decisive actions and product enhancements, providing business teams with actionable insights and investigating issues to empower leadership decisions. Embedded within a dynamic environment, you will design, execute, and analyze experiments to solve complex business problems directly related to growth and success. Close collaboration with stakeholders will be key to your success, as you address challenges and contribute to the continuous improvement of the user experience. We currently have multiple Decision Scientist II roles open across different teams. Please note, we will start with a more general interview process and will then match you accordingly based on interest and experience.

Requirements

Bachelor's degree in a quantitative field such as Mathematics, Computer Science, Operations Research, Economics, or equivalent experience.
3+ years of experience in product analytics, business operations, analytics, growth marketing, or product.
Proficient with A/B testing, experimental design, and utilizing statistical modeling and causal inference to inform business decisions.
Proficient in statistical computing and scripting languages such as Python (numpy/pandas/matplotlib), R, and SQL.
Structured analytical approach to problem-solving, with the ability to turn complex problems into clear analytical tasks.

Nice To Haves

Advanced degree (Master’s or Ph.D.) in a quantitative field such as Mathematics, Computer Science, Operations Research, or Economics.
Extensive knowledge and practical experience in statistical methods such as causal inference, experimental design, and Bayesian inference.
Advanced skills in R or Python, and experience with machine learning models.

Responsibilities

Define KPIs and create reports and dashboards against large data sets to track performance.
Use data to identify opportunities for improving user acquisition and optimizing return on investment.
Turn ambiguous questions into clear analytical problems and solve them using data.
Become deeply familiar with product data, understanding its limitations and caveats, to support development and growth.
Design, execute, and analyze experiments that drive product growth and improvement.
Create readable and informative data visualizations, documentation, and presentations to communicate insights to stakeholders and executives.