Vodafone Idea - Senior Data Scientist - Advanced Analytics & AI

: Senior Data Scientist (Telecom Domain) Location: Mumbai, India Department: Advanced Analytics & AI Position Overview: We are seeking a highly skilled Senior Data Scientist to design, build, and scale our next-generation AI/ML platforms. In this role, you will leverage telecom data to architect production-ready personalization and recommendation engines. You will lead the integration of Generative AI and Agentic frameworks within our secure AWS cloud ecosystem. Key Responsibilities: 1. AI/ML Development & Personalization: - Design and deploy high-performance recommendation systems to drive customer retention, ARPU (Average Revenue Per User), and cross-selling. - Build advanced machine learning (ML), deep learning (DL), and natural language processing (NLP) models to parse complex network and customer interactions. - Architect and implement cutting-edge Generative AI solutions and autonomous Agentic AI frameworks to automate complex customer and operational workflows. 2. Data Engineering & Production Pipelines: - Construct, optimise, and maintain robust data pipelines and production-grade ML pipelines (MLOps) for real-time and batch processing. - Work closely with data engineers to transform massive, unstructured telecom datasets into clean feature stores. 3. Cloud Architecture & Systems Design: - Own the end-to-end ML lifecycle on AWS Cloud, utilizing services like SageMaker, EMR, Glue, Lambda, and Bedrock. - Design scalable, fault-tolerant AI architectures that cleanly integrate with core telecom network systems. 4. Analytics & Visualisation: - Perform deep-dive exploratory data analysis to uncover commercial and operational trends. - Present complex model metrics and business KPIs to executive leadership using interactive dashboards and reporting tools. Required Technical Skills: 1. Core Programming: - Elite Python skills with absolute mastery of data science libraries (NumPy, Pandas, Scikit-Learn, PyTorch, or TensorFlow). 2. Big Data & Querying: - Advanced proficiency in PySpark for distributed computing, alongside expert-level SQL skills for handling relational and non-relational databases. 3. Generative & Agentic AI: - Hands-on experience building multi-agent systems using frameworks like LangChain, CrewAI, AutoGen, or LlamaIndex. 4. Cloud Infrastructure: - Strong working knowledge of AWS environments, IAM policies, and cloud data warehousing. 5. Data Visualisation: - Proficiency in building clean visual stories using tools like Tableau, Power BI, QuickSight, or advanced Excel. Qualifications & Experience: - Experience: Minimum 5 years of professional data science experience, with a proven track record of shipping ML products to production. - Domain: Previous experience in the Telecom sector handling Call Detail Records (CDR), subscriber behaviour, or churn modeling is highly preferred. - Education: Bachelors or Masters degree.