Staff Data Scientist

CLEAR - Corporate•New York, NY

2d•Hybrid

About The Position

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 38 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. As CLEAR scales, we’re investing deeply in data, experimentation, and analytics to improve how we make decisions and serve our members. We’re looking for a Staff Data Scientist to join our Analytics team. This is a high-impact, high-autonomy individual contributor role for someone who wants to develop a culture of science, knows how to connect business priorities to data, and has a passion for shipping high-quality work that drives business outcomes.

Requirements

10+ years of experience working in data science or adjacent fields, preferably in B2B SaaS or subscription businesses.
A graduate degree in Economics, Statistics, Computer Science, Data Science, or a related quantitative field. A PhD is a strong signal, but not a strict requirement.
Deep expertise in causal inference, experimentation, and machine learning models. You are the person others come to when the measurement problem is hard.
Exceptional communication skills, both written and verbal, with the ability to distill complex quantitative work into crisp, actionable insights for technical and non-technical audiences alike.
Strong command of SQL, Python or R, and the data engineering ecosystem. You can write a production pipeline in a pinch.
Excited to contribute to a team culture centered around curiosity, humility, and impact.

Responsibilities

Own the design, execution, and interpretation of experiments and causal analyses that drive decisions on user acquisition, activation, retention, and reengagement.
Establish and defend the methodological standards (A/B testing, guardrail metrics, measurement frameworks) that ensure we learn reliably from every test.
Develop and maintain user growth forecasting systems.
Partner with Finance, Marketing, and Product to deliver credible, timely forecasts of key growth metrics and ensure leadership has the quantitative foundation to set targets and allocate resources.
Drive analytics strategy within Growth, including the metrics layer, self-serve dashboards, and the infrastructure that enables the broader team to operate with data fluency.
Translate complex analytical findings into clear narratives for senior leadership.
Influence strategic decisions through a combination of technical depth and effective communication.
Collaborate across organizational boundaries with Product Management, Engineering, Design, Marketing, and Finance to embed data science into every phase of product development and marketing strategy.
Stay current on advances in applied economics, statistical methodology, machine learning, and AI, and bring those advances into the team's practice where they create real value.