Staff Business Analyst

About Ethos
Ethos is a leading life insurance technology company on a mission to protect families by democratizing access to life insurance and empowering agents at scale. With its robust three-sided technology platform, Ethos is transforming the life insurance experience for consumers, agents, and carriers alike. Ethos offers instant, accessible products and a seamless online process that requires no medical exams and just a few health questions; it eliminates traditional barriers, making it easier than ever for everyone to protect their families. Ethos is redefining how life insurance is bought, sold, and underwritten.
About the role
The Ethos Marketing team is a centralized, multi-disciplinary group of marketers, strategists, designers, storytellers, and makers who work across product groups and functions. We are designing the future and the today of the Ethos brand through every interaction within and outside of the product.
We are looking for a sharp, curious analyst who can go beyond dashboards and reporting to genuinely investigate how our offline and direct mail channels perform digging into attribution methodology, data layers, and vendor models rather than just consuming their output. This role sits at the intersection of business analytics and data science: you'll be trusted to build models, stress-test vendor and attribution assumptions, and proactively surface answers to business questions before anyone has to ask.
We need someone who can pick up real modeling and investigative work, not just BI support, to help the team keep pace with a growing offline and direct mail testing roadmap.
Duties and Responsibilities
- Investigate channel performance and business questions proactively, don't wait for a ticket to identify what's off, what's an opportunity, or what needs a deeper look
- Go deep into attribution and underlying data layers to diagnose discrepancies, validate vendor claims, and evaluate new attribution or measurement vendors
- Build models (e.g., response/lift models, allocation logic, simple regressions) to support offline and direct mail decision-making
- Support the scaling of direct mail testing: manage multi-cell test mail merges and data pulls, dashboarding, and analysis to guide list selection and optimization
- Develop easy-to-consume dashboards and frameworks to monitor and visualize KPIs
- Communicate findings and insights to key stakeholders and influence channel managers to take action based on your recommendations

Qualifications & Skills
Required:
- 5+ years of experience in business intelligence, analytics, or data science at well-established firms or high-growth tech startups
- 3+ years of experience building and maintaining BI reporting in a tool like Hex or Mode on a regular basis
- 3+ years of experience working with SQL on a regular basis
- Experience building statistical or predictive models outside of pure dashboard work
- Experience working with Python for data analysis and model-building
- Comfort working with ambiguous, incomplete, or conflicting data; attribution and vendor data are rarely clean
- Strong written and verbal communication skills; able to translate technical findings into recommendations non-technical stakeholders can act on
- A self-starter mentality, this role requires identifying problems and opportunities, not just executing on requests

Preferred:
- Experience with experimentation and Bayesian measurement
- Experience with direct mail, offline, or other non-digital marketing channels
- Experience with dbt or maintaining data pipelines/marts
- Familiarity with statistical techniques such as difference-in-difference, incrementality testing, and general linear models

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The US national base salary range for this full-time position is $127,000 - $223,000. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the positio