About Arkero

Arkero is an AI company building intelligent automation solutions for professional sports organizations, ticketing platforms, and live entertainment businesses. We were founded on the conviction that the passionate professionals running these institutions deserve tools that amplify their expertise, not slow them down.

Our AI works alongside sports professionals, automating repetitive workflows so teams can focus on strategy, creativity, and the decisions that drive real business impact. If you're excited about applying cutting-edge AI to one of the most data-rich industries in the world, we'd love to hear from you.

The Role

We are seeking a highly skilled and innovative Senior Full Stack Data Scientist to join our dynamic team. The ideal candidate will possess a strong background in both data science and software engineering, with a focus on developing end-to-end data-driven solutions. This role offers an exciting opportunity to leverage advanced analytics and cutting-edge technologies to drive impactful business outcomes. You'll work across the full data science lifecycle: from data acquisition and feature engineering to model development, dashboard delivery, and stakeholder communication.

Key Responsibilities

• Design, develop, and deploy end-to-end AI and machine learning solutions — from data acquisition and feature engineering through model training, validation, and production deployment.
• Build and maintain robust data pipelines for acquiring, cleaning, and preprocessing large-scale datasets from varied and often messy sources, with a strong focus on data quality and reliability.
• Leverage AI and advanced analytics techniques to develop innovative, scalable solutions that drive impactful business outcomes.
• Optimize model and AI system performance through feature engineering, hyperparameter tuning, rigorous validation, and continuous monitoring — treating calibration and drift as ongoing operational concerns.
• Build scalable, maintainable software to integrate AI and data science workflows with existing systems, enabling seamless data-driven decision-making across the organization.
• Establish and maintain monitoring mechanisms to proactively detect model drift, data quality issues, and performance degradation — identifying root causes and validating fixes.
• Work closely with engineers, software developers, and business stakeholders to translate ambiguous business questions into structured AI-driven analyses with explicit assumptions and clear, audience-appropriate communication.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
• 7+ years of hands-on experience across the full data science stack — from raw data acquisition and feature engineering to model deployment and production monitoring.
• Experience with Claude Code, Codex, or other AI coding agents in delivering high quality data science work.
• Strong proficiency in Python and SQL, with a solid foundation in software engineering best practices including version control, maintainable code, and working effectively in a shared codebase.
• Deep understanding of machine learning algorithms, statistical modeling, and model validation — with proven experience productionizing ML models including drift detection, calibration, and performance monitoring.
• Demonstrated experience with generative AI and large language models, including prompt engineering, fine-tuning, or integrating AI APIs into production workflows.
• Experience developing and deploying end-to-end data science solutions in cloud environments, with familiarity across the modern AI/ML tooling ecosystem.
• Strong written and verbal communication skills — able to translate complex AI-driven findings into clear, actionable insights for both technical and non-technical audiences.

Preferred Qualifications

• Experience on a small or startup team — comfortable wearing engineering, analyst, and PM hats in the same week.
• Experience with sports and ticketing platforms and data ecosystems such as Ticketmaster, SeatGeek, or similar.