AI Data Scientist

Photon; Dallas (TX); On-site; USD 180,000 - 260,000; Full time

Job summary

Photon seeks an experienced AI Data Scientist to lead evaluation, monitoring, and optimization of AI-powered solutions in production environments. The candidate should have 11–15 years of experience with deep expertise in ML, Generative AI, model validation, and data science, focusing on quality, reliability, safety, and business impact.

A key requirement is hands‑on experience in building an AI-driven Digital Financial Guidance Platform, including advisory or wealth management features.

Qualifications

• Hands-on experience building AI-driven financial guidance components is required.
• Strong background in evaluating AI/ML model quality, safety, and governance.

Responsibilities

• Design frameworks to evaluate AI/ML models for accuracy, quality, safety, and compliance.
• Develop scoring methodologies and validation techniques for Generative AI and predictive models.
• Define model performance metrics including accuracy, precision, recall, F1-score, hallucination rates and drift.
• Establish AI quality standards for production deployment and monitoring.
• Monitor production AI systems for drift and performance degradation, identifying risks.
• Build automated monitoring, alerting, and reporting for AI model health.
• Conduct root-cause analysis of model issues and implement improvements.
• Drive continuous optimization through data-driven insights and experimentation.

Skills

Machine Learning

Generative AI

Model Validation

Data Science

Job description

We are seeking an experienced AI Data Scientist with 11–15 years of experience to lead the evaluation, monitoring, and optimization of AI-powered solutions in production environments. The ideal candidate will possess deep expertise in Machine Learning, Generative AI, Model Validation, and Data Science, with a strong focus on ensuring model quality, reliability, safety, and business impact.

A mandatory requirement for this role is hands‑on experience working on a project that involved building an AI‑driven Digital Financial Guidance Platform, including AI‑powered customer advisory, financial coaching, wealth management assistance, or financial recommendation systems.

This role requires close collaboration with Product, Engineering, Risk, Compliance, and Business teams to build trusted AI systems that deliver personalized financial guidance while adhering to regulatory and governance requirements.

• Design and implement frameworks to evaluate AI and machine learning models for accuracy, quality, safety, and compliance.
• Develop scoring methodologies, benchmarking processes, and validation techniques for Generative AI, LLMs, and predictive models.
• Define model performance metrics including accuracy, precision, recall, F1-score, hallucination rates, and drift indicators.
• Establish AI quality standards and best practices for production deployment.
• Monitor production AI systems to identify model drift, performance degradation, and emerging risk patterns.
• Build automated monitoring, alerting, and reporting mechanisms for AI model health.
• Conduct root-cause analysis of model issues and implement improvement strategies.
• Drive continuous optimization through data-driven insights and experimentation.