About the company
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Data Analyst based in United States.
As a Lead Data Analyst, you will play a strategic role in turning complex data into decisions that shape both product direction and customer outcomes.
Responsibilities
- Own end-to-end measurement for new product initiatives, including defining success metrics, supporting instrumentation, and analyzing adoption, engagement, retention, and other key outcomes.
- Identify opportunities to automate, scale, and improve data processes, governance, and recurring analytical workflows.
- Serve as a data subject-matter expert, helping internal teams understand and effectively use data in their decision-making.
- Partner with product managers, designers, and engineers throughout the product lifecycle, using insights to inform strategy, improve user journeys, and guide product development.
- Collaborate with customer success and sales teams to demonstrate product impact, develop customer-facing analyses, and create compelling narratives for QBRs and executive reviews.
- Investigate employee health, wellbeing, and customer trends to uncover opportunities for product, data, and customer experience improvements.
- Translate complex datasets and analytical findings into concise, actionable insights that can be understood by technical and nontechnical stakeholders.
- Work collaboratively with other analysts to establish a holistic approach to stakeholder data needs and contribute to long-term analytics strategy.
- Mentor and coach analysts, share best practices, and help elevate the team's technical and analytical capabilities.
- Take ownership of ambiguous projects and develop scalable solutions that address both immediate business needs and longer-term operational improvements.
Requirements
- 5+ years of experience as a product analyst, customer analyst, or in a closely related analytical role, ideally within a fast-paced startup, health-tech, or B2B SaaS environment.
- Demonstrated experience managing customer-facing or senior stakeholder relationships, with backgrounds in consulting, B2B SaaS, or similar environments particularly relevant.
- Strong hands-on SQL experience, with experience applying SQL transformations through dbt preferred.
- Experience using Python or R for data analysis and statistical work.
- Familiarity with modern data-stack technologies; experience with Databricks, dbt, and Looker is particularly relevant.
- Experience building, maintaining, or improving automated systems and processes for recurring data requirements is preferred.
- Ability to transform complex datasets into clear, practical insights and communicate findings effectively to executives, customers, engineers, and other audiences.
- Strong understanding of analytical methodologies, data processes, and measurement frameworks, with an ability to connect metrics to broader business and product objectives.
- Proven ability to identify opportunities for better data governance, more efficient workflows, and scalable analytical solutions.
- Highly self-directed and comfortable taking ownership of projects from definition through delivery in an environment where priorities and requirements may be ambiguous.
- Collaborative mindset with strong stakeholder-management, communication, mentoring, and problem-solving skills.
Conditions
- Competitive base compensation: $145,000–$175,000, with the final offer determined by experience, expertise, and other relevant factors.
- Additional compensation: Performance bonus and equity as part of the overall compensation package.
- Health coverage: Medical, dental, and vision insurance.
- Retirement benefits: 401(k) program with company match.
- Generous paid time off: Programs designed to support meaningful time away from work and recovery.
- Thrive Time: Additional paid time off following major projects or particularly intensive work periods to encourage genuine rest and recharge.
- Remote work: Remote position based in the United States.
- Mission-driven environment: Opportunity to contribute to technology focused on improving health, wellbeing, resilience, and performance at scale.
- Career development: Opportunity to grow professionally while helping shape data strategy, analytics practices, and business growth.
- Inclusive culture: A supportive, human-centered environment committed to equal opportunity and a welcoming workplace.