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Mid-level, popular Data Scientist role in metro market increases competition.
Strong marketing-science and causal-inference focus increases industry-specific background sensitivity.
Explicit 5+ years, advanced statistical qualifications, and specialized causal marketing skills make filters strict.
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Develop, validate, and deploy advanced regression-based causal inference models for marketing measurement and ROI analysis.
Design and analyze experiments including A/B tests, multivariate, and geo-experiments to generate actionable business insights.
Collaborate cross-functionally with product, engineering, and marketing science to integrate models into scalable production systems and contribute to research initiatives.
Master’s or PhD in Computer Science, Statistics, Mathematics, Econometrics, or related quantitative field.
Strong expertise in causal inference techniques and marketing science measurement methods.
5+ years of experience in data science or applied statistics, preferably in marketing analytics.
Proficiency in Python or R, SQL, and cloud-based data platforms; experience deploying models into production with large-scale data pipelines.
Experienced in complex regression modeling, Bayesian approaches, and connecting causal inference to practical marketing decisions like budget allocation and channel optimization.
Able to interpret academic research and translate it into scalable, practical implementations.
Has a strong focus on statistical rigor, experimentation design, and scientific collaboration in a fast-growing SaaS environment.