About Ethos
Ethos (Nasdaq: $LIFE) 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
#LI-Remote #LI-MK1
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 position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
Please note that the compensation details listed in US role postings reflect the base salary only and do not include applicable bonus, equity, or benefits.
You can find further details of our US benefits at ethoslife.com Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. At Ethos we are dedicated to building a diverse, inclusive and authentic workplace.
We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Pursuant to the SF Fair Chance Ordinance, we will consider employment for qualified applicants with arrests and conviction records.
To learn more about what information we collect and how it may be used, please refer to our California Candidate Privacy Notice .
Recruitment Notice: Please be aware of recruitment scams. All legitimate communication from our team will only come from email addresses ending in @ethos.com or @getethos.com. We will never ask for payment, banking details, or sensitive personal information during the hiring process. If you are contacted by someone claiming to represent us from a different email address, please treat it as fraudulent.
Requirements
Must-haves
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
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
Nice-to-haves
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
#LI-Remote #LI-MK1
Please note that the compensation details listed in US role postings reflect the base salary only and do not include applicable bonus, equity, or benefits.
To learn more about what information we collect and how it may be used, please refer to our California Candidate Privacy Notice .
Application prep
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