Director of AI & Adv Analytics

OneBlood•Saint Petersburg, FL

10d

About The Position

Provides strategic and technical leadership for the organization's AI, ML, and advanced analytics capabilities. This role defines the vision, roadmap, and standards for AI-driven innovation, leads a team of AI/ML engineers and data scientists, and partners with business and technology leaders to deliver scalable solutions that generate insights, improve decision-making, optimize operations, and create measurable business value.

Requirements

Bachelor’s degree (preferred Masters of Science) in Computer Science, Analytics, or related field from an accredited college or university.
Ten (10) years of progressive experience in data engineering, data science, or a related role, with hands-on experience building and deploying machine learning models, including three (3) or more years in a technical leadership or management capacity leading AI/ML teams and delivering enterprise-scale initiatives.
Advanced knowledge in Python, SQL, machine learning frameworks, and modern analytics technologies used for model development, deployment, and optimization
Advanced knowledge of generative AI technologies, including AI agents, multi-agent systems, prompt engineering, embeddings, vector databases, and Retrieval-Augmented Generation architectures
Advanced knowledge in supervised and unsupervised machine learning techniques, model evaluation, feature engineering, and performance measurement methodologies
Proficient in cloud-based AI and analytics platforms, data architectures, data warehousing, and ETL/ELT processes
Strong knowledge of model customization approaches, including supervised fine-tuning, retrieval-augmented fine-tuning, and parameter-efficient training methods
Proficient in MLOps, model monitoring, lifecycle management, observability, governance, and responsible AI practices
Proficient in establishing engineering best practices, including version control, code reviews, testing, CI/CD, and collaborative development standards
Advanced statistical knowledge in hypothesis testing, experimental design, forecasting, causal inference, regression analysis, and uncertainty quantification
Demonstrates strong leadership, strategic planning, organizational development, and change management capabilities
Ability to communicate, engage stakeholders, and demonstrate executive presentation skills and translate complex technical concepts into business value
Ability to lead enterprise AI initiatives, managing budgets and vendors, and delivering measurable business outcomes through AI, machine learning, and advanced analytics solutions.

Responsibilities

Provides strategic leadership for the organization's AI, machine learning, and advanced analytics capabilities and establishes the vision, roadmap, standards, and operating model for AI-driven innovation
Directs the design, development, deployment, and lifecycle management of AI solutions, machine learning models, intelligent agents, and advanced analytics applications that address complex business challenges
Oversees the development of generative AI capabilities, including Retrieval-Augmented Generation (RAG), foundation model customization, vector search technologies, embeddings, and enterprise knowledge integration
Establishes enterprise standards for agent orchestration, model evaluation, MLOps, monitoring, governance, and responsible AI practices that ensure scalable and reliable solutions
Leads the application of advanced statistical methods, predictive modeling, experimentation, forecasting, and analytical techniques that support strategic decision-making and operational improvement
Partners with business, product, and technology leaders and aligns AI/ML priorities, capabilities, and delivery roadmaps with organizational objectives and measurable business outcomes
Directs the development of AI-ready data assets, feature engineering capabilities, and model training frameworks that support machine learning and generative AI initiatives
Establishes and enforces governance, security, compliance, documentation, and quality standards that promote transparency, reproducibility, and responsible AI adoption
Drives performance management and optimization activities across AI models, platforms, and operational processes to maximize accuracy, efficiency, business value, and cost effectiveness
Manages AI/ML infrastructure, cloud services, vendor relationships, budgets, and resource planning to ensure secure, scalable, and efficient operations
Builds, leads, and develops a high-performing team of AI/ML engineers, data scientists, and analytics professionals through coaching, mentoring, talent development, and performance management
Evaluates emerging technologies, industry trends, and market developments and advances the organization's AI, machine learning, and advanced analytics capabilities.