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Director Of Data Science Jobs in Tennessee (NOW HIRING)

Lead end-to-end delivery of large-scale, cross-functional data science projects. * Facilitate solution design workshops, technical reviews, and stakeholder discovery sessions. * Define project scope ...

Lead end-to-end delivery of large-scale, cross-functional data science projects. * Facilitate solution design workshops, technical reviews, and stakeholder discovery sessions. * Define project scope ...

Showing results 21-40

Director Of Data Science information

See Tennessee salary details

$49K

$140.6K

$221.5K

How much do director of data science jobs pay per year?

As of Sep 3, 2026, the average yearly pay for director of data science in Tennessee is $140,565.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,800.00 and $172,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by a director of data science when leading cross-functional teams?

As a Director of Data Science, one of the key challenges is aligning the goals of data science teams with those of product, engineering, and business stakeholders. This often involves translating complex technical findings into actionable insights that non-technical colleagues can understand and use. Additionally, managing resource allocation and prioritizing projects across multiple departments can be demanding, especially in fast-paced environments. Building a collaborative culture and fostering open communication are crucial for overcoming these challenges and ensuring data-driven strategies deliver business value.

What are the key skills and qualifications needed to thrive as a director of data science, and why are they important?

A Director of Data Science needs advanced expertise in statistical analysis, machine learning, and data strategy, typically supported by a graduate degree in a quantitative field and significant industry experience. Familiarity with big data platforms (e.g., Hadoop, Spark), programming languages (Python, R), and cloud-based analytics tools, as well as experience managing data science teams, is essential. Strong leadership, communication, and business acumen are key soft skills for aligning technical work with organizational goals and influencing stakeholders. These skills are crucial for driving data-driven decision-making and maximizing the strategic impact of data science initiatives within the organization.

What is the difference between Director Of Data Science vs Data Scientist?

AspectDirector Of Data ScienceData Scientist
Required CredentialsAdvanced degrees (Master's or PhD), leadership experienceBachelor's or Master's in Data Science, Computer Science, or related fields
Work EnvironmentStrategic planning, team management, cross-department collaborationData analysis, model development, coding, and experimentation
Employer & Industry UsageTech companies, finance, healthcare, large enterprisesStartups, tech firms, research institutions, various industries

The main difference between a Director Of Data Science and a Data Scientist lies in their scope of responsibilities. The Director oversees strategic initiatives, manages teams, and aligns data projects with business goals, while Data Scientists focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but the Director's role emphasizes leadership and strategic planning.

What does a director of data science do?

A director of data science oversees data science teams, develops strategies for data analysis and modeling, and ensures the implementation of data-driven solutions to support business goals. They often manage projects, collaborate with other departments, and have expertise in statistical methods, machine learning, and data management tools. Strong leadership, communication skills, and experience with programming languages like Python or R are essential for this role.

What are the most commonly searched types of Of Data Science jobs in Tennessee?

The most popular types of Of Data Science jobs in Tennessee are:

What cities in Tennessee are hiring for Director Of Data Science jobs?

Cities in Tennessee with the most Director Of Data Science job openings:

Infographic showing various Director Of Data Science job openings in Tennessee as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $140,565 per year, or $67.6 per hour.

Director, Clinical Data & AI

SMITH & NEPHEW SNATS INC

Memphis, TN โ€ข On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 21 days ago


Key responsibilities

  • Define and execute the global strategy for Clinical Data & AI aligned to evidence-generation and AI transformation goals.

  • Own the design, governance, and evolution of clinical data platforms, data pipelines, and interoperability frameworks.

  • Lead development and deployment of AI/ML capabilities across the clinical lifecycle, including data quality automation, analytics, and model development.


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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