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Remote Advanced Ai Data Trainer Jobs in Tennessee

Remote micro1 is engaging Medical Writers / Clinical Document Authors to participate in a customer ... advanced AI-assisted writing tools for clinical documentation. In this role, you'll apply your ...

Remote micro1 is engaging Medical Writers / Clinical Document Authors to participate in a customer ... advanced AI-assisted writing tools for clinical documentation. In this role, you'll apply your ...

Remote micro1 is engaging Medical Writers / Clinical Document Authors to participate in a customer ... advanced AI-assisted writing tools for clinical documentation. In this role, you'll apply your ...

Remote micro1 is engaging Medical Writers / Clinical Document Authors to participate in a customer ... advanced AI-assisted writing tools for clinical documentation. In this role, you'll apply your ...

Remote micro1 is engaging Medical Writers / Clinical Document Authors to participate in a customer ... advanced AI-assisted writing tools for clinical documentation. In this role, you'll apply your ...

Remote micro1 is engaging Medical Writers / Clinical Document Authors to participate in a customer ... advanced AI-assisted writing tools for clinical documentation. In this role, you'll apply your ...

Remote micro1 is engaging Medical Writers / Clinical Document Authors to participate in a customer ... advanced AI-assisted writing tools for clinical documentation. In this role, you'll apply your ...

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Remote Advanced Ai Data Trainer information

What is a remote advanced AI data trainer?

A Remote Advanced AI Data Trainer is a professional who works remotely to create, label, and refine data used to train artificial intelligence (AI) models. They ensure the data is accurate and relevant, often working with complex datasets and advanced AI algorithms. Their tasks may include annotating text, images, or audio, as well as providing feedback to improve AI performance. This role requires strong attention to detail, familiarity with AI concepts, and the ability to work independently from any location.

What are the key skills and qualifications needed to thrive as a remote advanced AI data trainer?

To thrive as a Remote Advanced AI Data Trainer, you need strong analytical skills, a solid understanding of machine learning concepts, and a relevant degree or experience in data science or computer science. Familiarity with data annotation tools, AI training platforms, and programming languages like Python is often required. Excellent attention to detail, communication, and problem-solving abilities help set top performers apart in this role. These skills ensure high-quality data labeling and training, directly impacting the accuracy and effectiveness of AI systems.

What are some common challenges faced by remote advanced AI data trainers, and how can they be addressed?

Remote Advanced AI Data Trainers often encounter challenges such as maintaining clear communication with global teams, managing complex annotation guidelines, and ensuring data quality while working independently. To address these, it’s important to establish regular check-ins, use collaborative tools for feedback, and stay updated on best practices for data labeling. Proactively asking questions and participating in team discussions can also help ensure consistency and clarity in your work.

What is the difference between Remote Advanced Ai Data Trainer vs Remote AI Data Annotator?

AspectRemote Advanced Ai Data TrainerRemote AI Data Annotator
CredentialsTypically requires experience in AI, machine learning, or data science; certifications in data labeling or AI tools are commonOften requires basic data labeling skills; certifications are less common
Work EnvironmentRemote, collaborative with AI teams, involves training models and refining data setsRemote, focused on labeling and annotating data sets, often solo tasks
Industry UsageUsed in AI development, machine learning projects, and data science teamsUsed across industries for preparing training data for AI models

The Remote Advanced Ai Data Trainer and Remote AI Data Annotator roles both involve working with data for AI projects. However, the trainer typically requires more specialized knowledge, including AI concepts and model training experience, whereas the annotator focuses on labeling data. The trainer's role is more collaborative and involves refining AI models, while the annotator primarily performs data preparation tasks.

What are popular job titles related to Remote Advanced Ai Data Trainer jobs in Tennessee?

For Remote Advanced Ai Data Trainer jobs in Tennessee, the most frequently searched job titles are:

What job categories do people searching Remote Advanced Ai Data Trainer jobs in Tennessee look for?

The top searched job categories for Remote Advanced Ai Data Trainer jobs in Tennessee are:

What cities in Tennessee are hiring for Remote Advanced Ai Data Trainer jobs?

Cities in Tennessee with the most Remote Advanced Ai Data Trainer job openings:

Infographic showing various Remote Advanced Ai Data Trainer job openings in Tennessee as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution.

Director, Clinical Data & AI

Memphis, TN • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 11 days ago


Job description

Life Unlimited. At Smith+Nephew we design and manufacture technology that takes the limits off living. The Director of Clinical Data & AI is the global functional leader responsible for the strategy, architecture, and operational execution of clinical data and AI capabilities supporting end-to-end evidence generation. This role owns the clinical data lifecycle-from data acquisition and management to advanced analytics, AI enablement, and synthetic/simulated data-ensuring all data assets are high-quality, interoperable, and fit-for-purpose for regulatory, scientific, and operational decision-making. The Director serves as the enterprise authority on clinical data platforms and AI-enabled evidence generation, driving integration across clinical systems, data engineering, AI/ML, and statistical/clinical programming. This position has full accountability for the strategy, execution, quality, and evolution of the Clinical Data & AI function globally.

What will you be doing?

1. Global Clinical Data & AI Strategy

  • Define and execute the global strategy for Clinical Data & AI aligned to enterprise evidence-generation and AI transformation goals
  • Establish a unified operating model integrating:
    • Clinical systems (EDC, eCOA, registries)
    • Clinical Data Lake & central data model
    • Data management and data engineering
    • AI/ML and advanced analytics
  • Serve as the enterprise authority on clinical data architecture and AI enablement for clinical & medical affairs across all BUs and geographies
  • Partner with Clinical Study Management, Clinical Strategy, Regulatory, Medical Affairs, Statistics, and IT to define data-driven evidence strategies

2. Clinical Data Architecture & Platforms

  • Own the design, governance, and evolution of:
    • Clinical Data Lake (CDL) and standardized data models
    • Clinical systems ecosystem (EDC, eCOA, registry ingestion, integrations)
    • Data pipelines, transformation, and interoperability frameworks
  • Ensure scalable, compliant, and extensible architecture supporting:
    • Cross-study analytics
    • Real-world data integration
    • Device + clinical data linkage
  • Drive standardization (e.g., CDISC-based models) and elimination of data silos

3. AI, Data Science & Advanced Analytics

  • Lead development and deployment of AI/ML capabilities across the clinical lifecycle, including:
    • Data quality automation and monitoring
    • AI-assisted clinical study reporting and analytics
    • Cross-study insights and meta-analyses
  • Drive integration of AI into core workflows, not point solutions
  • Establish best practices for:
    • Model development, validation, monitoring
    • Responsible AI (traceability, reproducibility, regulatory alignment)
  • Oversee collaboration between data science, statistics, and programming teams

4. Synthetic Data, Simulation & Virtual Twins

  • Own strategy and execution for:
    • Synthetic clinical data generation
    • Simulation frameworks for study design and operational planning
    • Virtual twin development for patient- and study-level modeling
  • Ensure alignment with regulatory expectations for transparency and scientific validity
  • Integrate synthetic and simulated data into:
    • Study design optimization
    • Evidence generation (e.g., hybrid designs, external controls)

5. Clinical Data Management & Quality

  • Oversee global clinical data management function, ensuring:
    • High-quality, consistent, and inspection-ready data
    • Efficient study startup (eCRF design, database builds) and closeout
    • Risk-based monitoring and analytics-driven data review
  • Embed AI, machine learning modeling, and automation into CDM workflows to improve efficiency and quality
  • Ensure alignment with regulatory and compliance standards (FDA, EU MDR, GDPR, HIPAA)

6. Statistical & Clinical Programming Integration

  • Own alignment and integration of:
    • Statistical programming (TFLs, ADaM outputs)
    • Clinical programming (data pipelines, transformations)
  • Ensure seamless data flow from raw data analysis-ready datasets reporting
  • Drive standardization, automation, and reuse across studies and programs
  • Leverage AI solutions to accelerate programming across Global Clinical and Medical Affairs

7. Operational Excellence & Delivery Model

  • Own intake, prioritization, and delivery across:
    • Data platform initiatives
    • AI/ML programs
    • Study-level data operations
  • Implement scalable delivery models for standardized multi-source clinical outcomes datasets from the Clinical Data Lake to key business stakeholder teams
  • Optimize resourcing across:
    • High-throughput standardized work
    • High-complexity AI/data science initiatives

8. Regulatory & Data Governance Leadership

  • Ensure all clinical data and AI activities are:
    • Compliant with global regulatory requirements
    • Traceable, auditable, and reproducible
  • Establish strong governance across:
    • Data standards and lineage
    • AI model lifecycle
    • Data privacy and security
  • Support regulatory submissions with robust, defensible data strategies

Key Interfaces

  • Global Clinical Research Operations leadership
  • Clinical / Medical Affairs / Regulatory Affairs
  • Statistics, Data Science, and AI teams
  • IT / Digital / Enterprise Data organizations
  • External partners, CROs, AI vendors, and regulators

Education

  • BA required, PhD (preferred) or Master's in Data Science, Biostatistics, Computer Science, or related field

What will you need to be successful?

  • Minimum of 10 years experience across clinical data, AI/ML, and data platforms in medtech/pharma/biotech
  • Proven leadership of multi-domain teams (data management, engineering, data science, AI, programming)
  • Demonstrated ownership of enterprise data architecture (e.g., data lake/platform) - Databricks preferred
  • Strong track record supporting regulatory submissions and clinical evidence generation
  • Enterprise mindset - integrates data, AI, and operations into a unified capability
  • Technical depth + breadth - credible across data engineering, CDM, AI, and analytics
  • Regulatory credibility - understands how data and AI decisions impact submissions
  • Execution rigor - delivers scalable, high-quality platforms and outputs
  • Transformational leadership - embeds AI into workflows, not as isolated innovation
  • Pragmatic innovation - advances capabilities while maintaining compliance and reliability

You Unlimited.

  • The anticipated base compensation range for this position is $165,250-$236,000USD annually. The actual base pay offered to the successful candidate will be based on multiple factors, including but not limited to job-related knowledge/skills, experience, and geographic location. Compensation decisions are dependent upon the facts and circumstances of each position and candidate. In addition to base pay, we offer competitive bonus and benefits, including medical, dental, and vision coverage, 401(k), tuition reimbursement, medical leave programs, parental leave, generous PTO, paid company holidays, 8 hours of volunteer time annually, and a variety of wellness offerings such as EAP.

  • Inclusion + Belonging: Committed to Welcoming, Celebrating and Thriving. Learn more about our Employee Inclusion Groups on our website https://www.smith-nephew.com/

  • Your Future: 401k Matching Program, 401k Plus Program, Discounted Stock Options, Tuition Reimbursement

  • Work/Life Balance: Flexible Personal/Vacation Time Off, Paid Holidays, Flex Holidays, Paid Community Service Day

  • Your Wellbeing: Medical, Dental, Vision, Health Savings Account (Employer Contribution of $500+ annually), Employee Assistance Program, Parental Leave, Fertility and Adoption Assistance Program

  • Flexibility: Hybrid Work Model (For most professional roles)

  • Training: Hands-On, Team-Customized, Mentorship

  • Extra Perks: Discounts on fitness clubs, travel and more!

Smith+Nephew provides equal employment opportunities to applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability.

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