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Strong employer brand, metro location, mid-level ML role, and broad skill requirements increase applicant competition.
Core ML and production skills transfer broadly, but streaming retention domain expertise adds medium specificity.
Explicit 3+ years requirement plus mandatory SQL, Python, PySpark, and production ML experience.
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Build and deploy machine learning models focused on customer retention, churn prediction, and lifetime value for streaming products.
Conduct exploratory data analysis to identify behavioral drivers of retention and generate actionable insights.
Collaborate with cross-functional teams to translate retention challenges into scalable data-driven solutions and promote ML adoption.
Minimum 3+ years experience in building machine learning products and personalization.
Proficiency in SQL, Python (pandas), and PySpark for large distributed datasets.
Strong knowledge of statistical tests, classical ML algorithms (e.g. regression, boosting, GBM), and model optimization.
Bachelor's or Master's degree in Computer Science, Statistics, Data Science, or related field.
Experienced in customer retention analytics including churn prediction, survival analysis, and LTV modeling.
Skilled in production ML pipeline deployment and working with large-scale streaming or subscription-based product data.
Capable of leading technical decisions and effectively communicating technical solutions across teams including product and engineering.