Data Scientist II (ML Engineering)

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 continues to scale, we’re deepening our investment in the data science ecosystem that powers our products, personalization, and decision-making. We’re looking for a Data Scientist to design, develop, and deploy advanced statistical and machine learning models that drive measurable business impact on our digital identity platform. This is a hands-on individual contributor role for someone who blends strong modeling expertise, exceptional Python engineering craft, familiarity with modern ML tooling, and a passion for translating complex data into clear, actionable intelligence. You’ll build and operationalize models that help CLEAR understand, predict, and optimize behavior across our digital identity platform delivering insights and automation that scale.

What You'll Do:

• Evolve CLEAR’s predictive modeling ecosystem: design, train, and optimize statistical and machine learning models for our digital identity platform that support product, risk, fraud, operations, and member experience teams.
• Develop high-quality production code including enhancements to feature engineering pipelines, model training workflows, and evaluation frameworks that meet reliability and performance standards.
• Partner with Data Engineering and ML Platform teams to deploy models into production and ensure real-time and batch inference systems run efficiently.
• Advance CLEAR’s AI & ML capabilities by designing reusable modeling components, improving model documentation, and contributing to a roadmap for integrating ML into core products and decision flows.
• Improve experimentation and insight generation by building robust tooling and analytical frameworks, designing statistical tests, and synthesizing results into clear and actionable recommendations for cross-functional teams.

What You Bring:

• 3+ years of experience in data science, machine learning, or applied statistics within a modern cloud data environment like AWS Sagemaker.
• Advanced Python with deep experience in scientific libraries (e.g. pandas, NumPy, SciPy, matplotlib), machine learning frameworks (e.g. scikit-learn, XGBoost, LightGBM, pytorch), and model evaluation tooling.
• SQL skills and experience working with cloud data warehouses (e.g. Snowflake, BigQuery, Redshift).
• Experience with modern ML workflow tools (e.g., Airflow, Dagster, MLflow, Vertex / SageMaker, Voxel 51).
• Understanding of statistical methods, experiment design, data cleansing, feature engineering, and model interpretability.
• Experience deploying production models and maintaining them through their lifecycle (monitoring, retraining, performance management).
• Strong communication and storytelling skills; you can translate complex data science work into insights and decisions.
• A proactive, curious mindset with a passion for standardization, repeatability, and scaling high-quality modeling practices.

Why You’ll Love This Role:

• High-impact: Your models and insights will shape decision-making and member experiences across CLEAR.
• Craft + influence: Blend hands-on modeling with the opportunity to set the bar for data science excellence company-wide.
• Mission-driven culture: Help build trusted, secure, frictionless experiences for millions.
• Autonomy: Build cutting-edge solutions while helping to guide best practices
• Culture that moves: We value curiosity, iteration, direct feedback, and bold thinking.

How You’ll be Rewarded:

At CLEAR, we help YOU move forward - because when you’re at your best, we’re at our best. You’ll