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Mid-level, generalist data scientist role with common skills and marketing-agency appeal, high applicant competition.
Role requires marketing-measurement expertise (MMM, ADH, GA4), so cross-industry transferability is limited.
Explicit 2–5 years plus mandatory Python, SQL, GCP, and marketing-model experience increases filtering strictness.
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Build and maintain predictive models such as lead scoring and churn prediction to support marketing and sales decisions.
Design and execute Media Mix Modeling studies to measure marketing channel effectiveness and advise budget allocation.
Develop and productionize data pipelines and models using Python and SQL in Google Cloud Platform, delivering actionable insights to clients.
Proficiency in Python (pandas, scikit-learn, statsmodels) for data analysis and machine learning.
Strong SQL skills with experience handling large, complex datasets.
Experience with Google Cloud Platform, especially BigQuery, cloud functions, and data workflows.
2–5 years of relevant data science or analytics experience; Bachelor’s/Master’s degree in a quantitative field.
Experienced in building lead scoring, churn prediction, and media mix modeling for marketing analytics.
Capable of translating complex statistical models into clear, business-relevant recommendations for marketing and media teams.
Familiar with media and marketing performance concepts and comfortable working in cross-functional teams involving client servicing and media planning.