V2Soft
Data Scientist
Seattle, Washington, USA · Mid · contract, third party
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About the role
- We are seeking a Data Scientist with a strong background in marketing measurement, causal inference, and experimentation who has deep passion for building data-driven products, ability to formulate data insights and scientific vision, and a proven track record of executing complex projects and delivering business impact.
Responsibilities
- Marketing Measurement: Develop and enhance Marketing Mix Models (MMM) to measure channel effectiveness, optimize budget allocation, and quantify ROI across marketing investments.
- Customer Lifetime Value (CLV): Build and refine CLV models to inform acquisition targeting, retention strategies, and customer segment prioritization.
- Causal Inference & Experimentation: Design, execute, and analyze A/B tests and quasi-experiments (e.g., geo holdouts, difference-in-differences, synthetic controls) to measure incremental lift of marketing campaigns.
- Campaign Optimization: Partner with marketing teams to translate measurement insights into actionable recommendations for targeting, creative, and channel mix.
- Develop and enhance Marketing Mix Models (MMM) to measure channel effectiveness, optimize budget allocation, and quantify ROI across marketing investments.
- Build and refine CLV models to inform acquisition targeting, retention strategies, and customer segment prioritization.
- Design, execute, and analyze A/B tests and quasi-experiments (e.g., geo holdouts, difference-in-differences, synthetic controls) to measure incremental lift of marketing campaigns.
- Partner with marketing teams to translate measurement insights into actionable recommendations for targeting, creative, and channel mix.
Nice to have
- Experience programming in Python, R, or related language.
Benefits
- Cross-functional Collaboration: Work with data scientists, machine learning engineers, and business stakeholders to deliver measurement solutions to production.
This listing is sourced directly from V2Soft's careers page and normalized into a canonical job model.