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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.
Job Responsibility:
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
Requirements:
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
A proactive, curious mindset with a passion for standardization, repeatability, and scaling high-quality modeling practices
What we offer:
Comprehensive healthcare plans
Family-building benefits (fertility and adoption/surrogacy support)
Flexible time off
Annual wellness stipend
Free OneMedical memberships for you and your dependents
A CLEAR Plus membership
A 401(k) retirement plan with employer match
Catered lunches every day
Fully stocked kitchens
Stipends and reimbursement programs for well-being and learning & development