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: