About this opportunity
SupportFinity™ lists this Data Scientist II opportunity in new york, New York. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Have you ever had that green-light feeling? When you hit every green light and the day just feels like magic. CLEAR's mission is to create frictionless experiences where every day has that feeling. With more than 30+ million passionate members and hundreds of partners around the world, CLEAR’s identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or right on your phone, CLEAR connects you to the things that make you, you - unlocking easier, more secure, and more seamless experiences - making them all feel like magic.
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 work with talented team members motivated by our mission of making experiences safer and easier. Our offices are bright and energetic with an open concept and plenty of conference rooms and casual co‑working spaces. We also offer catered lunches every day and have fully stocked kitchens. Outside of the office, we invest in your well‑being and learning & development with stipends and reimbursement programs.
We offer holistic total rewards, including 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, and a 401(k) retirement plan with employer match. The base salary range for this role is $150,000 -$180,000, depending on levels of skills and experience.
The base salary range represents the low and high end of CLEAR’s salary range for this position. Salaries will vary depending on various factors which include, but are not limited to location, education, skills, experience and performance. The range listed is just one component of CLEAR’s total compensation package for employees and other rewards may include annual bonuses, commission, Restricted Stock Units.
CLEAR provides reasonable accommodation to qualified individuals with disabilities or protected needs. Please let us know if you require a reasonable accommodation to apply for a job or perform your job. Examples of reasonable accommodation include, but are not limited to, time off, extra breaks, making a change to the application process or work procedures, policy exceptions, providing documents in an alternative format, live captioning or using a sign language interpreter, or using specialized equipment.
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Worksite address
new york, NY, 10261, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.