Data & AI Analyst

Alcanza Clinical Research • Lake Mary, FL

2h

About The Position

Alcanza is a growing multi-site, multi-phase clinical research company with a network of locations in AL, AZ, FL, GA, IL, MA, MI, MO, NV, SC, TX, VA, and Puerto Rico. We have established a strong presence across Phase I-IV studies and several therapeutic areas including vaccine, neurology, dermatology, psychiatry, and general medicine. Join us as we continue to grow.

The Data & AI Analyst supports the design, testing, deployment, and continuous improvement of AI‑enabled solutions that enhance patient recruitment, clinical operations, quality, and business workflows across a multi‑site clinical research network. This role focuses on applied AI, especially LLM‑enabled workflows, automation, and decision support—ensuring solutions are reliable, explainable, compliant, and usable by support and site-based teams.

The AI Analyst partners with operations, quality/QA, recruitment, finance, and IT to identify AI opportunities, translate them into testable solutions, evaluate performance, and operationalize them safely in a regulated environment (HIPAA/GCP/21 CFR expectations.

Requirements

• Bachelor’s degree or equivalent experience in analytics, computer science, informatics, engineering, or related field, and 2+ years related work experience, or an equivalent combination of education and experience, is required.
• Must have strong ability to translate business workflows into testable AI solutions.
• Must have hands‑on experience with at least one of: · LLM/prompting workflows, automation tools, or applied ML · SQL/BI analytics and data manipulation
• Strong technical literacy.
• Proven ability in converting complex use cases into simple solutions, supporting development of custom applications on platforms, and/or building out AI-enabled enterprise solutions
• Demonstrated proficiency in data and AI technologies and software product development; strong understanding of AI-enabled software development lifecycle (SDLC), product steering, product management best practices, LLM workflow design, multi-model solutions, and related commercial applications
• Demonstrated success in supporting enterprise projects and cross-functional initiatives in clinical research and / or healthcare
• Broad understanding in technical subject matters such as IT operations, cloud operations and security, IT engineering and systems administration in clinical research and / or healthcare
• Broad knowledge of HIPAA, 21 CFR Part 11, GCP, data privacy regulations and frameworks in clinical research and / or healthcare
• Strong organizational, time management, problem solving, and project management skills to meet firm deadlines.
• Executive-level written and verbal communication and presentation skills
• Well-developed interpersonal and listening skills and the ability to work well independently and collaboratively within a team environment, building trusted relationships with clients and sponsors, and with all levels within the organization.
• Well-developed strategic, analytical and problem-solving capabilities
• Ability to effectively handle multiple tasks and adapt to changes in workloads and priorities
• Must possess a high degree of professionalism, integrity, dependability, respect of others, self-motivation, and exemplify a strong work ethic.
• Ability to handle highly sensitive information in a confidential and professional manner.
• May be required to travel up to 10% of the time, dependent on business needs.

Nice To Haves

• Additionally, experience evaluating AI outputs and setting human‑in‑the‑loop controls, and basic Python and/or experience with analytics notebooks is preferred.
• Experience in clinical research, healthcare operations, or regulated environments and familiarity with clinical research concepts (protocols, source documentation, audits, data integrity expectations) is preferred.
• Experience with clinical research systems (CTMS, eSource, eRegulatory) and / or health information systems (EHRs, EMRs, Practice Management) and broad understanding of HIPAA, GCP, FDA 21CFR Part 11, and / or key frameworks and regulations applicable to clinical research is preferred.

Responsibilities

• Continuously stay current with emerging data, AI, and analytics innovations, assessing their relevance and responsible application within a regulated clinical research environment.
• AI Use Case Discovery & Requirements (Business-to-Technical): identify high‑value AI opportunities in workflows such as recruitment operations, compliance checks, audit readiness, and administrative processes.
• Gather requirements from stakeholders and translate them into clear problem statements, success metrics, and acceptance criteria.
• Produce lightweight artifacts (use case briefs, workflow maps, risk notes) to guide build/test cycles.
• LLM Workflow Design (Human-in-the-Loop): Design and iterate LLM‑supported workflows for document understanding and knowledge retrieval (e.g., summarization, classification, extraction, Q&A), with strong attention to “human review” steps for clinical appropriateness.
• Build prompt templates, structured output formats, and validation logic for consistent results.
• Support AI use cases like LLM review of clinical notes/source documents for compliance and audit readiness (where approved), aligning with the organization’s stated opportunities.
• Model & Output Evaluation (Quality, Reliability, Safety): Create evaluation plans and test sets (representative examples, edge cases, failure modes).
• Measure performance using agreed metrics (accuracy, precision/recall where applicable, extraction fidelity, reviewer agreement).
• Track and analyze errors; propose changes to prompts, data inputs, and workflow guardrails.
• Maintain documentation of evaluation results to support internal QA expectations and inspection readiness principles (risk focus, documentation, traceability).
• Assist in identifying “low risk / high volume” opportunities to reduce manual effort, consistent with the organization’s interest in automating tedious workflows.
• Produce AI‑supported insights that help teams prioritize work, understand constraints, and improve action and decision-making across the study lifecycle and patient journey to deliver operational efficiency and quality (within policy and privacy rules).
• Follow data governance standards for handling sensitive data (PHI/PII).
• Ensure AI workflows meet organizational expectations around HIPAA/GCP/21 CFR Part 11 awareness (working with IT/QA for controls).
• Participate in the AI-powered product development lifecycle and support automation for back‑office and operational processes (e.g., routing, triage, reconciliation support, drafting standardized responses, generating checklists).
• Stakeholder Enablement & Adoption: Create training materials and user guidance for AI tools and support deployment of said solutions across the organization (what it does, what it doesn’t do, review steps, escalation paths)
• Gather user feedback and usage patterns; drive iterative improvements.
• Communicate outcomes clearly to non‑technical teams (what changed, why it matters, how to use it).
• Documentation & Operational Excellence: document prompt versions, workflow logic, evaluation results, and release notes.
• Support change management and “release discipline” to avoid disruption to site operations.
• Perform other duties as assigned to support organizational goals.

Benefits

• Full-time employees regularly scheduled to work at least 30 hours per week are benefits-eligible, with coverage starting on the first day of the month following date of hire.
• Medical, dental, vision, life insurance, short and long-term disability insurance, health savings accounts, supplemental insurances, and a 401k plan with a safe harbor match are offered.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level