
Senior Analytics Engineer, Finance
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Job Description
About us:
LifeMD is a leader in virtual primary care, headquartered in NYC, and we're redefining how healthcare meets technology. Our vertically integrated digital care platform powers telemedicine, laboratory services, and pharmacy solutions, serving over 200 conditions across all 50 states.
Recognized as one of the fastest-growing healthcare tech companies (#166 on Deloitte Fast 500 in 2023), LifeMD is not just a healthcare company-it's a tech company revolutionizing healthcare.
About the role:
The Senior Analytics Engineer, Finance is a SQL expert with a background in financial data and analytics. This role will bridge analytics and finance, playing a pivotal role in revenue recognition, financial data management, and supporting strategic initiatives like the automation of revenue processes and revenue recognition from point of sales to integration into the financial systems. The ideal candidate has experience across accounting and data engineering; strong technical expertise and problem solving skills; and the ability to synthesize complex data transformations for stakeholders.
Key Responsibilities:
Process Automation and Accounting Support
- Update and maintain revenue recognition calculations, ensuring compliance with accounting standards.
- Collaborate with the accounting and finance teams to ensure accuracy and timeliness of reporting for internal purposes, executive presentations, and audits and financial statements.
- Serve as the primary technical and business point of contact for revenue process automation projects.
Financial Data Management and Analytics
- Manage financial data requests and projects, such as inventory projections, quarterly earnings support, and ad-hoc analyses.
- Develop and maintain financial dashboards and reporting tools that provide actionable insights to executive leadership.
- Ensure data accuracy, integrity, and consistency across financial systems and reports.
- Proactively monitor key financial metrics and generate insights to inform strategic decision-making.
Data Ingestion and Manipulation
- As needed, write code and design ingestion strategies to fetch data from source systems and prepare it for analysis.
- Design, build, and document data pipelines to lay the groundwork for consistent reporting and enable ad-hoc analyses.