Staff Business Analyst

Ethos is a life insurance technology company transforming how life insurance is bought, sold, and underwritten through a technology platform serving consumers, agents, and carriers. The Staff Business Analyst will investigate offline and direct mail channel performance, build statistical and predictive models, evaluate attribution methodologies and vendors, and provide actionable insights to marketing stakeholders.

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

Requirements:

• 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
• 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