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Lead Data Analyst

Parachute Health

HybridHybrid

Original Job Summary

Overview

Nearly half of patients needing medical equipment at discharge don’t get it in time due to an inefficient, fax-driven process. Parachute Health is on a mission to drive efficiency through digital connectivity and deliver a delightfully simple ordering experience for clinicians.

Role Summary

The Lead Data Analyst drives data-driven decision-making across the organization. In this role, you will lead high-impact analyses, mentor the analytics team, and partner with stakeholders to solve complex business problems.

Responsibilities

  • Analytical Leadership: Lead cross-functional analyses, design analytical frameworks, and ensure data rigor.
  • Project & Team Leadership: Manage high-complexity initiatives, translate data into actionable insights, and mentor team members.
  • Strategic Contribution: Partner with leadership to identify data-driven opportunities and promote a culture of experimentation.

Qualifications

  • Bachelor's degree in Computer Science, Data Science, or related field.
  • 7+ years of experience in data analysis or business intelligence.
  • 1+ years in a senior leadership role.
  • Expertise in SQL, Python, and experience with modern data stacks (BigQuery, Snowflake, Redshift).
  • Advanced experience with BI tools (Looker or similar) and data visualization.

Benefits

  • Medical, Dental, and Vision Coverage
  • 401(k) Retirement Plan
  • Remote-first company with NYC office option
  • Equity Incentive Plan
  • Annual Company-Wide Bonus, Flexible Vacation, and additional stipends

Key skills/competency

  • Data Analysis
  • SQL
  • Python
  • BI Tools
  • Leadership
  • Data Visualization
  • Analytical Frameworks
  • Cloud Data Warehouse
  • Mentoring
  • Strategic Insight

How to Get Hired at Parachute Health

🎯 Tips for Getting Hired

  • Research Parachute Health: Understand their mission, platform, and healthcare impact.
  • Customize your resume: Emphasize SQL, Python, and BI tools proficiency.
  • Highlight leadership: Focus on mentoring and cross-team collaboration experience.
  • Prepare for interviews: Practice explaining complex data projects clearly.

📝 Interview Preparation Advice

Technical Preparation

Practice SQL query optimization.
Review Python statistical packages.
Build sample Looker dashboards.
Study cloud data warehouse principles.

Behavioral Questions

Describe a challenging leadership experience.
Explain cross-functional team collaboration.
Share mentoring success stories.
Discuss handling ambiguous problems.