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Tier-1 employer and Bangalore metro increase competition; senior, niche ML/LLM requirements moderate it.
Core ML skills transfer broadly, but subscriptions/payments and LLM product experience require domain-specific fit.
Explicit 9+ years plus mandatory ML/LLM, MLOps, and payments/subscriptions experience makes filtering strict.
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Design, develop, and deploy machine learning models and decision systems to accelerate subscription growth via D2C and B2B/partner channels.
Analyze large datasets to extract actionable insights that shape acquisition, retention, and subscription strategies at scale.
Collaborate cross-functionally to integrate models into production, run A/B tests, and drive data-driven business impact on a platform with 250M+ subscriptions.
9+ years of hands-on experience in applied machine learning or data science, preferably in subscription, payments, or consumer-facing revenue-impact roles.
Master's or PhD in Computer Science, Statistics, Mathematics, or related quantitative field.
Expert-level proficiency in Python and SQL; familiarity with modern ML frameworks such as Scikit-learn, TensorFlow, PyTorch, and big data/cloud platforms (Spark, AWS SageMaker, GCP Vertex AI).
Strong statistical foundations including causal inference, experimental design, and experience deploying end-to-end ML systems.
Senior data scientist with deep expertise in churn prediction, propensity modeling, LLMs, and production ML deployment within subscription or payments ecosystems.
Operates effectively at the intersection of data science and product to drive measurable business outcomes and stakeholder alignment.
Experienced mentor capable of guiding junior team members and communicating complex technical findings clearly to technical and non-technical audiences.