Director of AI & Adv Analytics

OneBlood seeks a Director of AI & Adv Analytics in St Petersburg, Florida, to provide strategic and technical leadership for its AI, machine learning, and advanced analytics capabilities. The director will set the vision, roadmap, standards, and operating model for AI-driven innovation and lead teams delivering scalable solutions that improve insights, decisions, operations, and measurable business outcomes.

Responsibilities

• Direct the design, development, deployment, and lifecycle management of machine learning models, intelligent agents, and advanced analytics applications. Oversee generative AI capabilities, including retrieval-augmented generation, foundation model customization, vector search, embeddings, and enterprise knowledge integration.
• Establish standards for agent orchestration, model evaluation, MLOps, monitoring, governance, security, compliance, documentation, quality, and responsible AI. Develop AI-ready data assets, feature engineering capabilities, and model training frameworks.
• Lead statistical analysis, predictive modeling, experimentation, and forecasting. Optimize model and platform accuracy, efficiency, cost, and business value; manage AI/ML infrastructure, cloud services, vendors, budgets, and resources.
• Partner with business, product, and technology leaders to align delivery with organizational objectives. Build and develop teams of AI/ML engineers, data scientists, and analytics professionals; assess emerging technologies.

Qualifications

• Bachelor’s degree in Computer Science, Analytics, or a related field from an accredited institution; a Master of Science is preferred. Requires 10 years of progressive experience in data engineering, data science, or a related role, including hands-on machine learning model development and deployment, and at least 3 years leading AI/ML teams and enterprise-scale initiatives in a technical leadership or management capacity.
• Advanced knowledge of Python, SQL, machine learning frameworks, generative AI, supervised and unsupervised learning, model evaluation, and feature engineering. Proficiency in cloud AI and analytics platforms, data architecture, warehousing, ETL/ELT, MLOps, monitoring, governance, and responsible AI; knowledge of model fine-tuning and parameter-efficient training.
• Strong statistical expertise in hypothesis testing, experimental design, forecasting, causal inference, regression, and uncertainty quantification. Ability to establish engineering practices for version control, code reviews, testing, and CI/CD, and to lead strategy, change, stakeholders, vendors, and budgets. No certificates or licenses are required.

The posting lists a full-time position. Work may involve light physical effort handling objects up to 20 pounds; duties are regularly performed indoors.