Staff Analytics Lead - Offline & Direct Mail Attribution

Ethos Life; New York (NY); On-site; USD 110,000 - 165,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k) retirement plan

Company equity

Paid time off & holidays

Leave programs for new parents

Job summary

Ethos Life is seeking a sharp analyst to go beyond dashboards, digging into attribution methodology, data layers, and vendor models for offline and direct mail channels. You’ll build models, stress-test assumptions, and surface answers before questions are asked.

You’ll work at the intersection of business analytics and data science, developing frameworks, dashboards, and actionable insights to guide marketing decisions across product groups.

Qualifications

• 3+ years of experience with SQL on a regular basis.
• 5+ years in business intelligence, analytics, or data science at firms or startups.
• Experience with Python for data analysis and model-building.
• Experience building statistical or predictive models beyond dashboards.
• Strong written and verbal communication to translate findings for non-technical stakeholders.
• Experience with experimentation and Bayesian measurement.
• Familiarity with direct mail, offline, or non-digital marketing channels.
• Knowledge of data pipelines/marts and data reliability considerations.
• Comfort with ambiguous or incomplete data and attribution challenges.

Responsibilities

• Investigate offline and direct mail channel performance and attribution models.
• Build models to support decision-making on testing roadmaps and vendor claims.
• Develop dashboards and frameworks to monitor KPIs for stakeholders.
• Describe findings clearly and influence channel managers to act on recommendations.
• Scale direct mail testing, multi-cell mail merges, and data pulls.

Skills

SQL

Python

Data modeling

Statistical modeling

Experimentation

Attribution analysis

Communicating insights

Bayesian methods

Data visualization

Tools

Hex

Mode

dbt

Job description

Ethos Life is seeking a sharp analyst to go beyond dashboards, digging into attribution methodology, data layers, and vendor models for offline and direct mail channels. You’ll build models, stress-test assumptions, and surface answers before questions are asked.

You’ll work at the intersection of business analytics and data science, developing frameworks, dashboards, and actionable insights to guide marketing decisions across product groups.