AI Brand Lift Measurement Engineer

Farion Data

Remote · $130k – $160k / year · Full-time · Posted 4 months ago

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About the role

Brand advertising is notoriously difficult to measure. Conversion attribution captures last-click sales. It doesn't capture the awareness campaign that made the brand recognizable when the prospect finally converted six weeks later. Brand lift measurement — quantifying the causal impact of brand advertising on awareness, consideration, and preference metrics — is the measurement methodology that closes this gap. We serve 90 enterprise brand marketers with attribution and measurement infrastructure. Brand lift measurement is the capability that makes brand spend defensible: connecting advertising exposure to survey-measured awareness changes with proper control group design, handling the confounding from organic search and PR activity, and delivering measurement results that finance teams accept as credible evidence of brand investment ROI. You'll lead the brand lift measurement platform: designing experiment infrastructure for clean treatment-control assignment, implementing causal inference methods that handle imperfect randomization in real-world media buys, building survey integration for pre/post awareness measurement, and creating the measurement reports that brand teams use to optimize their mix of performance and brand investment.

Fully remote.

Responsibilities

Design brand lift experiment infrastructure with clean treatment-control assignment for media buy contexts
Implement causal inference methods handling imperfect randomization in real-world digital media
Build survey integration measuring pre/post awareness, consideration, and preference for exposed and control groups
Develop multi-touch brand lift attribution for campaigns spanning multiple channels and timeframes
Create measurement reports quantifying brand investment ROI in terms finance teams accept
Validate lift estimates against independent measurement sources where available

Requirements

6+ years in marketing measurement, causal inference, or media mix modeling
Deep understanding of brand lift measurement methodology and experiment design for advertising
Strong Python and statistical computing skills with survey data analysis experience
Experience with causal inference under imperfect randomization: IV, difference-in-differences, synthetic control
Track record delivering brand measurement results that change how clients allocate brand spend