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AI Data Scientist

PhotonDallas, TX🇺🇸United States

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationDallas, TX, United States
Generative AIMachine Learning

Job description

Job Title: AI Data Scientist
Location: Dallas, TX

Role Overview

We are seeking an experienced AI Data Scientist with 5 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.

Key Responsibilities AI Model Evaluation & Governance

  • 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.

AI Monitoring & Continuous Improvement

  • 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.

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