Marketing Data Scientist - Causal Inference & Experiments

Talentify; Seattle (WA); On-site; USD 84,000 - 98,000; Full time

Job summary

Talentify seeks a Data Scientist in Seattle, WA, onsite, with a strong background in marketing measurement, causal inference, and experimentation to build data-driven products and deliver business impact.

You will tackle MMMs, CLV modeling, and robust A/B testing, partnering with data scientists, ML engineers, and business stakeholders to productionize measurement solutions and drive growth across campaigns.

Qualifications

• PhD or Master's degree with 4+ years in CS/ML/Statistics/Economics.
• 3+ years building ML models or developing algorithms for business applications.
• Experience with causal inference methods (A/B testing, difference-in-differences, instrumental variables, propensity scoring, synthetic controls).
• Familiarity with cloud computation (AWS: S3, SageMaker, EMR, EC2).
• Experience programming in Python, R, or a related language.

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 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.
• Cross-functional Collaboration: Work with data scientists, ML engineers, and business stakeholders to deliver measurement solutions to production.

Skills

Causal Inference

Experiment Design

Cloud Computing Experience

Education

PhD or Master's degree

Job description

Talentify seeks a Data Scientist in Seattle, WA, onsite, with a strong background in marketing measurement, causal inference, and experimentation to build data-driven products and deliver business impact.

You will tackle MMMs, CLV modeling, and robust A/B testing, partnering with data scientists, ML engineers, and business stakeholders to productionize measurement solutions and drive growth across campaigns.