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Strong brand, popular mid-level Data Scientist title, and metro Hyderabad increase candidate competition.
Core ML, churn, and LTV modeling skills transfer across industries, though streaming subscription domain knowledge moderately matters.
Explicit 3+ years plus mandatory Python/SQL/PySpark, production ML pipelines, and modeling skills make filters strict.
Build and deploy machine learning models to predict and improve customer retention and long-term engagement for streaming products.
Conduct exploratory data analysis to identify behavioral drivers of churn and retention, delivering actionable insights for retention strategies.
Collaborate with cross-functional teams to translate retention challenges into scalable data-driven solutions and promote ML adoption across product and engineering teams.
3+ years of experience building machine learning products and personalization solutions.
Proficiency in SQL, Python (pandas), and PySpark; experience with large, distributed datasets.
Strong foundation in statistical tests and classical ML algorithms including regression, bagging, boosting, decision trees, and GBM.
Bachelor's or Master's degree in Computer Science, Statistics, Data Science, Quantitative field, or related discipline.
Experience specifically in churn prediction, survival analysis, or customer lifetime value (LTV) modeling within subscription or streaming domains.
Proven ability to lead technical decisions and effectively communicate complex technical solutions to both technical and non-technical stakeholders.
Hands-on experience with production ML pipelines, experimentation frameworks (like A/B testing), and familiarity with ML frameworks (TensorFlow, PyTorch, XGBoost, Scikit-learn).