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Mid-level Data Scientist, metro Mumbai, broad ML/AWS requirements and known telecom brand create high applicant competition.
Core ML, Python and AWS skills are transferable, though telecom marketing domain knowledge increases specificity.
Explicit 2–7 years plus mandatory hands-on ML, deep learning, AWS and degree/certification requirements yields high strictness.
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Develop predictive models and AI/ML solutions to impact customer revenue and Average Revenue Per User (ARPU).
Handle end-to-end data analysis including data gathering, exploratory data analysis, model development, and presenting results to business stakeholders.
Collaborate with BI, IT, and product teams to deploy AI/ML models on AWS cloud services and improve marketing verticals using data-driven approaches.
2-7 years of relevant work experience in data science or analytics.
Graduate, Master's, or PhD degree in Statistics, Economics, Engineering, or related quantitative discipline with exposure to AI/ML/Data Mining.
Hands-on expertise in Python programming, AWS tools (S3, EC2, EMR, Glue, SageMaker, Lambda, DynamoDB, Redshift, Quicksight), SQL scripting and machine learning frameworks (TensorFlow, Keras, etc).
Certification in Machine Learning, Deep Learning, Artificial Intelligence, or Data Science; AWS Cloud certifications preferred.
Experienced in building and deploying advanced AI/ML and deep learning solutions for large-scale telecom or marketing datasets to drive customer retention and ARPU improvements.
Strong proficiency in cloud computing architecture on AWS and ability to integrate data science workflows with cloud infrastructure.
Capable of combining statistical, econometric, and causal inference methods for designing experiments and evaluating models from both statistical and business perspectives.