LifeMD
Digital Healthcare
VP,Data&Analytics
“VP, Data & Analytics at LifeMD. Skills: Data platform ownership, Analytics engineering leadership, Revenue recognition accuracy, Financial modeling, AI analytics platform development. Own the full analytics stack. Manage a team of analytics engineers and analysts”
What You'll Achieve.
Ensure data accuracy and reliability; Drive AI insights; Amplify team output; Support earnings support, board materials, financial forecasts, and operational dashboards
Industry & Context.
Analytical skills
What They're Looking For.
Must Have
SQL at a senior level, dbt architecture, cloud warehouse experience, GCP production experience, BigQuery experience, Python fluency, Data engineering leadership experience, Experience managing small data or analytics engineering teams
Nice to Have
Experience with dbt modeling, incrementality, testing, and governance, Experience with GCP surrounding services such as GCS, Cloud Run, and Cloud Scheduler, Experience with revenue recognition at a public company, Experience contributing to financial modeling such as cohort forecasting, LTV, and unit economics, Experience architecting auditable data models, Experience representing the data function credibly to accounting, auditors, and finance leadership, Experience reading and modifying production code, Experience maintaining and extending data systems beyond the warehouse, including API integrations, scheduled jobs, and cloud infrastructure, Experience building internal tooling that uses LLMs, Experience using Claude Code, Cursor, or another AI-driven IDE for development, Experience actively shaping how AI gets woven into team workflows, Experience developing and retaining technical talent, Experience coaching individual contributors
What You'll Do.
Own the full analytics stack
Manage a team of analytics engineers and analysts
and architecture of revenue recognition data
Contribute directly to financial modeling
Maintain the in-house AI analytics platform
Develop new functionality using AI-driven tools
Surface insights with AI
Inform data architecture decisions
Produce data that supports strategy
Make recommendations based on data
How You'll Work.
Team & Collaboration
Partnering with Chief Accounting Officer; Collaborating with Finance, IT, and Security teams; Managing a team of analytics engineers and analysts organized by business function; Working closely with engineering teams; Working directly with the executive team
Communication Scope
Presenting insights to the executive team; Representing the data function directly to external auditors; Communicating with accounting, auditors, and finance leadership
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