Lead Advanced Analytics Specialist

2 days ago

Bengaluru, Karnataka, India beBeeTechnical Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Key Position: Technical Architect

Job Overview:

Our telecommunications organization requires a skilled professional to design and implement advanced analytical solutions. The ideal candidate will have expertise in churn prediction, intervention models, survival analysis, and customer lifetime value (CLTV) analysis.

This role demands technical leadership, with the ability to translate complex business problems into robust, scalable, and explainable analytical solutions for both consumer and enterprise customers.

Key Responsibilities:
  • Develop production-grade enterprise-level churn modeling solutions, incorporating classical ML and Deep Learning models.
  • Explore the integration of Large Language Models (LLMs) in predictive analytics for churn.
  • Design and implement intervention models to address identified churn risks proactively.
  • Apply Survival Analysis techniques to understand customer tenure and predict churn events.
  • Develop comprehensive Customer Lifetime Value (CLTV) analysis frameworks.
  • Conduct in-depth data analysis, including feature importance analysis and drift detection.
  • Implement model explainability techniques and ensure long-term accuracy and relevance of deployed models.

Requirements:

  • 8-10 years of experience in Solution Architecture with a focus on advanced analytics and machine learning.
  • Deep expertise in developing and deploying intervention models to mitigate churn.
  • Strong hands-on experience with Survival Analysis techniques for customer behavior prediction.
  • Extensive experience with Customer Lifetime Value (CLTV) analysis and its application in business strategy.

Desirable Skills:

  • Classical ML: Random Forest, Bagging & Boosting techniques, Ensemble models.
  • Deep Learning models for predictive analytics.
  • Experience with Large Language Models (LLMs) in predictive analytics.
  • Strong analytical skills with proven experience in feature importance analysis, model explainability, and drift detection.

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