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Well-known brand, mid-level generalist ML role, metro location, and broad skill requirements increase applicant competition.
Core ML and production skills are transferable, though retention and streaming domain experience add moderate specificity.
Explicit 3+ years requirement plus mandatory production ML, PySpark, SQL, and Python skills raises filter strictness.
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Build and deploy machine learning models focused on customer retention, churn prediction, and lifetime value to improve engagement with streaming products.
Conduct exploratory data analysis to identify behavioral drivers of churn and retention and translate findings into actionable insights.
Collaborate with cross-functional teams (Product, Design, Commerce, Content, Marketing) to align ML solutions with business retention challenges.
Bachelor's or Master's degree in Computer Science, Statistics, Data Science, Quant, or related field.
Minimum 3 years of experience building products with machine learning and personalization.
Proficient in SQL, Python (pandas), and PySpark for processing large distributed datasets.
Experience deploying production-scale ML pipelines and models, with strong understanding of classical ML algorithms and statistical testing.
Experienced in retention-focused analytics such as churn prediction, survival analysis, or LTV modeling.
Ability to lead technical decisions and communicate complex data science concepts effectively to cross-functional stakeholders.
Familiarity with large-scale data processing frameworks (Databricks, Apache Spark) and ML frameworks (TensorFlow, PyTorch, XGBoost, or Scikit-learn).