The VP of Data & Analytics oversees the entire data platform and analytics team, ensuring data reliability and driving AI insights for decision making across finance, marketing, and operations.
About us
LifeMD is transforming healthcare through intelligent digital experiences, AI-powered virtual care, and connected healthcare platforms. Our mission is to make high-quality healthcare more accessible, personalized, and convenient by combining world-class clinical care with modern technology and data-driven innovation.
As we continue to scale, we are investing in the next generation of AI, data, and platform capabilities that will fundamentally reshape how healthcare is delivered, experienced, and operated.
About the role
LifeMD is seeking a visionary and execution-focused Vice President of Data, Analytics & AI to lead the company’s enterprise data and artificial intelligence strategy. Reporting to the Chief Technology Officer, this executive will build the next-generation data and AI platform that powers every aspect of LifeMD—from patient experiences and clinical operations to internal productivity, intelligent automation, and business decision-making.
This is a hands-on Data engineering leadership role for someone who has successfully taken data and AI initiatives from proof of concept to enterprise production. The ideal candidate is equally comfortable discussing distributed data architectures, Retrieval-Augmented Generation (RAG), AI agents, LLM orchestration, analytics strategy, data engineering vision, and executive business priorities.
You will lead multidisciplinary teams across Data Engineering, Analytics Engineering, AI Engineering, Machine Learning, and Business Intelligence while partnering closely with Product, Engineering, Clinical Operations, Marketing, Finance, Compliance, and Security.
What You Will Own
Enterprise Data Platform
- Define and execute LifeMD’s enterprise data strategy and roadmap
- Build and scale modern cloud-native data platforms supporting operational, clinical, product, and financial workloads
- Design robust batch and real-time data pipelines across healthcare, product, pharmacy, CRM, marketing, finance, and operational systems
- Establish enterprise data models, governance, metadata management, and data quality frameworks
- Enhance self-service analytics and trusted enterprise reporting
Artificial Intelligence & GenAI
- Lead LifeMD’s enterprise AI strategy and production deployment roadmap
- Build secure enterprise Retrieval-Augmented Generation (RAG) platforms leveraging proprietary healthcare knowledge and enterprise content
- Design, deploy, and manage AI agents that automate clinical, operational, customer support, engineering, finance, HR, and internal business workflows
- Establish scalable LLMOps and AI engineering practices supporting multiple foundation models and vendors
- Lead evaluation, experimentation, and production deployment of emerging AI technologies
- Develop AI governance frameworks focused on safety, explainability, privacy, compliance, and responsible AI adoption
Knowledge Platforms & Intelligent Automation
- Build enterprise knowledge management capabilities supporting employees, providers, and customer-facing applications
- Develop internal AI copilots that improve productivity across engineering, customer care, operations, and clinical organizations
- Build intelligent search capabilities powered by vector databases and semantic retrieval
- Lead Model Context Protocol (MCP) architecture and governance to enable secure interoperability between AI models, enterprise systems, tools, and knowledge sources
- Drive automation initiatives that reduce manual work, improve operational efficiency, and accelerate decision-making
Data Engineering & Analytics
- Lead enterprise data engineering and analytics teams
- Build scalable ELT/ETL pipelines supporting healthcare operations and business intelligence
- Develop executive dashboards and real-time operational insights across patient engagement, provider performance, finance, product, marketing, and growth
- Establish KPIs and measurement frameworks supporting customer experience, healthcare outcomes, operational efficiency, and business performance
- Enable experimentation, predictive analytics, forecasting, and AI-driven decision support
Leadership
- Recruit, mentor, and develop high-performing teams across Data Engineering, Analytics Engineering, AI Engineering, Machine Learning, and Business Intelligence
- Foster a culture of experimentation, engineering excellence, innovation, continuous learning, and customer obsession
- Partner closely with Product Management, Engineering, Clinical Operations, Security, Legal, and Compliance to ensure scalable and compliant AI adoption
- Communicate technology strategy and business outcomes effectively to executive leadership and the Board of Directors
Requirements
- 12+ years of experience leading enterprise data, analytics, AI, or machine learning organizations
- 5+ years leading large engineering organizations responsible for enterprise data platforms and AI systems
- Proven experience deploying Generative AI solutions from proof of concept through enterprise production
- Deep expertise building Retrieval-Augmented Generation (RAG) architectures using vector databases, embeddings, enterprise knowledge repositories, and LLM orchestration frameworks
- Experience designing and deploying AI agents, workflow automation platforms, and intelligent assistants
- Strong understanding of MCP (Model Context Protocol), agent orchestration, prompt engineering, and modern AI application architectures
- Hands-on experience with modern cloud data platforms such as Snowflake, BigQuery, Databricks, or equivalent
- Strong programming experience in Python, SQL, APIs, distributed systems, and modern data engineering frameworks
- Experience with cloud-native architectures (AWS, Azure, or Google Cloud)
- Experience implementing LLMOps, MLOps, CI/CD, model evaluation, monitoring, observability, and governance frameworks
- Strong knowledge of healthcare data, HIPAA, PHI security, privacy, and regulatory compliance preferred
- Experience leading enterprise analytics, experimentation, KPI development, and executive reporting
- Exceptional communication, organizational, and executive leadership skills
Benefits
- Health Care Plan (Medical, Dental & Vision)
- Retirement Plan (Roth 401k)
- Life Insurance (Basic, Voluntary & AD&D)
- Flexible PTO Policy
- Paid Holidays
- Short Term Disability
- Training & Development
LifeMD New York, New York, USA Office
236 5th Ave 4th floor, New York, NY, United States, 10001
Similar Jobs
5 Days Ago
Fintech • Financial Services
Lead advanced data analytics and machine learning to monitor portfolio health, prevent fraud, build forecasting models, and identify performance improvements. Partner with business, product, technology, operations, and compliance to implement solutions, improve processes, drive strategic projects end-to-end, and present findings to executives.
Top Skills:
Machine LearningPython
7 Days Ago
Fintech • Financial Services
Work within Morgan Stanley's Business Solutions Group to deliver consulting engagements, program delivery, and data-driven analytics. Manage cross-functional projects, define problems, design data platforms, build dashboards and automation, analyze financial and operational data, and support ML/LLM initiatives including RAG and agentic workflows. Engage stakeholders, track risks and metrics, and prepare presentations for senior management.
Top Skills:
Agentic WorkflowsAutomation ToolsDashboardsData PipelinesExcelLlmsMachine LearningPower BIPowerPointPythonRRagTableau
Financial Services
Lead design, delivery, and support of risk data, reporting, and analytics solutions. Partner with stakeholders to improve risk measurement, data governance, automation, and reporting. Manage roadmaps, backlogs, documentation, observability, and a team delivering analytics, dashboards, and decision-support for regulatory, audit, and executive audiences.
Top Skills:
AgileAmazon RedshiftConfluenceMs ProjectOraclePostgresPower BIPythonQlikSharepointSmartsheetSnowflakeSQLTableauWaterfall
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
