Senior Data Science Engineer Visa Sponsorship Jobs in Tennessee
Tennessee's senior data science engineer job market spans healthcare analytics in Nashville, logistics and supply chain intelligence in Memphis, and advanced manufacturing research at Oak Ridge National Laboratory. Major employers including HCA Healthcare, FedEx, and Nissan North America have sponsored senior data science engineering roles, making Tennessee a competitive but accessible state for international candidates seeking visa sponsorship.
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INTRODUCTION
The Director, Data Science & AI Engineering will lead the development and execution of the Firm’s enterprise data science, analytics, and AI engineering strategy. This role is responsible for building and managing a multidisciplinary team of Data Scientists, Data Analysts, and MLOps / AI Engineers focused on delivering innovative, production-ready AI solutions that support the Firm’s legal and business operations. Key responsibilities include overseeing the design, implementation, and optimization of LLM-powered applications, retrieval-augmented generation (RAG) systems, AI agents, custom models, advanced analytics, and business intelligence platforms that provide actionable matter, financial, and operational insights to firm leadership.
This position serves as a strategic and hands-on leadership role within a rapidly evolving AI environment, responsible for establishing scalable architecture, governance, evaluation standards, security practices, and operational frameworks appropriate for a highly regulated professional services organization. The Director will work closely with the Knowledge Management & Innovation function and other firm stakeholders to translate legal and operational needs into practical AI-driven solutions that enhance efficiency, decision-making, and service delivery across the Firm.
KEY RESPONSIBILITIES
Leadership
- Design and implement the operational framework, team structure, delivery processes, and performance metrics for the firm’s Data Science & AI Engineering function.
- Recruit, develop, and lead a high-performing multidisciplinary team of Data Scientists, Data Analysts, and MLOps/AI Engineers, establishing strong technical and cultural standards.
- Oversee day-to-day team operations, including strategic planning, prioritization, project delivery, performance management, mentorship, and employee development.
- Foster a collaborative, innovative, and business-focused culture centered on delivering practical AI and analytics solutions that support legal and operational outcomes.
Build & Lead Internal AI Platforms and Solutions
- Design, develop, and deploy internal AI applications leveraging firm-approved large language models (LLMs), with a focus on scalability, evaluation, observability, and cost efficiency.
- Lead the development and management of the firm’s retrieval-augmented generation (RAG) capabilities, including ingestion pipelines, embeddings, vector and hybrid search, re-ranking, and citation-supported response generation across firm knowledge and matter data.
- Oversee integrations between AI applications and internal business systems, including document management, matter management, financial, timekeeping, and knowledge management platforms, utilizing secure and governed integration frameworks such as Model Context Protocol (MCP).
- Develop and operationalize AI-driven workflows and agent-based solutions that support legal and business processes, incorporating appropriate governance, controls, traceability, and human oversight.
- Direct model development, fine-tuning, evaluation, and optimization initiatives utilizing proprietary firm data while ensuring compliance with confidentiality, privilege, intellectual property, and security requirements.
- Lead the firm’s analytics and reporting initiatives, including data modeling, warehouse/lakehouse strategy, and the development of dashboards and business intelligence tools that provide actionable operational, financial, staffing, and AI utilization insights to firm leadership.
MLOps, Engineering Excellence, and Governance
- Establish and oversee core AI engineering and operational standards, including source control, CI/CD processes, infrastructure-as-code, observability, environment management, evaluation frameworks, and production support practices.
- Lead and maintain scalable MLOps/LLMOps capabilities, including prompt and model versioning, automated testing, performance monitoring, drift detection, latency and cost tracking, and incident management processes.
- Partner with Information Security, IT, Privacy, Risk, and the Office of General Counsel to ensure AI solutions comply with firm standards related to confidentiality, privilege, client obligations, data governance, and regulatory requirements.
- Support the development and execution of the firm’s AI governance framework, including acceptable use standards, vendor and model evaluation processes, testing protocols, and risk management practices.
- Evaluate and recommend build-versus-buy strategies for AI and technology solutions, leveraging commercial platforms where appropriate and developing custom solutions where the firm can achieve strategic or operational advantage.
Collaboration Across the Firm
- Collaborate closely with Knowledge Management & Innovation leadership to align AI development initiatives with practice group priorities, business needs, and user adoption strategies.
- Partner with attorneys, practice groups, and business stakeholders throughout the solution development lifecycle to ensure AI tools and workflows address operational and client service needs effectively.
- Communicate technical concepts, architectural decisions, and implementation trade-offs clearly and effectively to business and legal stakeholders.
- Represent the firm in interactions with vendors, clients, industry groups, peer organizations, and the broader legal AI community to support innovation, strategic partnerships, and talent development.
REQUIRED EDUCATION, KNOWLEDGE & EXPERIENCE
- Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Data Science, or a related quantitative field, or equivalent combination of education and relevant professional experience. Advanced degrees preferred.
- 10+ years of progressive experience in data science, machine learning, AI engineering, or a related technical discipline, including demonstrated leadership experience building and managing high-performing technical teams.
- Proven success designing, deploying, and supporting production AI/ML solutions, including large language model (LLM) applications, retrieval-augmented generation (RAG) systems, and agent-based workflows.
- Strong technical foundation with the ability to evaluate system architecture, engineering approaches, model performance, and technical design decisions across AI and analytics platforms.
- Deep understanding of modern AI technologies and architectures, including foundation models, embeddings, vector databases, hybrid search, RAG methodologies, agent frameworks, Model Context Protocol (MCP), prompt engineering, model evaluation, fine-tuning, and operational scalability considerations.
- Experience establishing and supporting MLOps/LLMOps practices, including cloud infrastructure, deployment automation, monitoring, security, and operational governance.
- Demonstrated experience leading enterprise analytics and business intelligence initiatives, including the development of executive-facing dashboards and reporting solutions that support strategic decision-making.
- Strong leadership, organizational, and problem-solving skills, with the ability to operate effectively in fast-paced, evolving, and highly collaborative environments.
- Excellent written and verbal communication skills, including the ability to communicate complex technical concepts, AI risks, and architectural decisions clearly to executive leadership, attorneys, and non-technical stakeholders.
- Sound judgment regarding AI governance, privacy, security, confidentiality, and ethical considerations associated with deploying AI technologies in regulated and data-sensitive environments.
PREFERRED SKILLS & QUALIFICATIONS
- Experience within the legal, professional services, financial services, or another highly regulated, document-intensive industry environment. Legal education or prior legal industry experience is a plus.
- Familiarity with legal technology and enterprise data platforms, including document management systems, matter and timekeeping systems, knowledge management platforms, eDiscovery technologies, and litigation support tools.
- Hands-on experience with AI platforms and tooling from providers such as OpenAI, Anthropic, Google, Microsoft, and open-source AI ecosystems, including familiarity with legal-specific AI platforms such as Harvey, CoCounsel, and Legora.
- Active participation in the AI engineering, machine learning, or applied research community through publications, speaking engagements, open-source contributions, or established industry networks.
Physical Requirements
- Ability to sit and stand for extended periods.
- Ability to lift up to 15 pounds.
Qualified applicants with arrest and conviction records will be considered for the position in accordance with the California Fair Chance Act.
The expected salary range for this position is $290,000 - $440,000. Final compensation will be determined based on several factors, including but not limited to, relevant experience, qualifications, skill set, and geographic location.
Pillsbury Winthrop Shaw Pittman LLP is an Equal Opportunity Employer.
If you require an accommodation in order to apply for a position, please contact us at PillsburyWorkday@pillsburylaw.com.
Senior Data Science Engineer Job Roles in Tennessee
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Search Senior Data Science Engineer Jobs in TennesseeSenior Data Science Engineer Jobs in Tennessee: Frequently Asked Questions
Which companies sponsor visas for senior data science engineers in Tennessee?
Healthcare and logistics companies lead sponsorship activity for senior data science engineers in Tennessee. HCA Healthcare and Vanderbilt University Medical Center sponsor roles in clinical data science and predictive analytics in Nashville. FedEx and its technology subsidiaries in Memphis hire for supply chain and operations data science. Oak Ridge National Laboratory and Tennessee Valley Authority also sponsor senior data science engineering positions, particularly for machine learning and energy systems work.
Which visa types are most common for senior data science engineer roles in Tennessee?
The H-1B visa is the most common visa for senior data science engineers in Tennessee, as the role consistently qualifies as a specialty occupation requiring a bachelor's degree or higher in computer science, statistics, or a related field. Candidates with advanced degrees may also encounter EB-2 pathways for permanent residence. Employers at federally funded institutions like Oak Ridge National Laboratory sometimes support J-1 visa or TN visas depending on candidate nationality and role structure.
How to find senior data science engineer visa sponsorship jobs in Tennessee?
Migrate Mate is the most direct way to find senior data science engineer visa sponsorship jobs in Tennessee. The platform filters specifically for roles where employers have demonstrated a history of sponsoring work visas, saving you from applying to positions where sponsorship is unlikely. Focus your search on Nashville's healthcare technology corridor and Memphis's logistics sector, where sponsorship activity for senior data science engineering roles is most concentrated.
Which cities in Tennessee have the most senior data science engineer sponsorship jobs?
Nashville accounts for the largest share of senior data science engineer sponsorship activity in Tennessee, driven by its healthcare IT sector and a growing technology startup scene. Memphis is the second most active city, with FedEx and related logistics companies hiring for data science roles in operations and supply chain optimization. Knoxville and the Oak Ridge corridor represent a smaller but consistent source of sponsorship, particularly for research-oriented senior data science engineering positions.
Are there state-specific factors that affect visa sponsorship for senior data science engineers in Tennessee?
Tennessee has no state income tax, which can affect how employers structure total compensation packages for sponsored roles, though this does not change the federal H-1B prevailing wage requirements that employers must meet. The state's concentration in healthcare, logistics, and advanced manufacturing means senior data science engineers with domain experience in those industries are particularly competitive. University pipelines from Vanderbilt University and the University of Tennessee in Knoxville also feed into local employer sponsorship programs.
What is the prevailing wage for sponsored senior data science engineer jobs in Tennessee?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.