Enterprise Data Science Senior Specialist

• Translate customer and product requirements into clear data science and AI implementation tasks
• Develop, train, test, and deploy ML/DL/GenAI and data pipelines aligned with customer‑specific use cases
• Ensure AI components are efficient, maintainable, and production‑ready, supporting smooth integration with enterprise systems and platforms
• Contribute to documentation, reproducibility, and knowledge transfer for implemented solutions
• Act as a subject‑matter contributor in machine learning, AI and GenAI engineering within delivery teams
• Apply best practices in feature engineering, model selection, evaluation, and optimization
• Support MLOps activities such as model versioning, monitoring, retraining, and performance tracking
• Participate in technical reviews, code reviews, and solution walkthroughs to maintain delivery quality
• Work closely with Enterprise teams to ensure AI solutions address real customer problems and deliver measurable outcomes
• Explain data science methods, assumptions, and results in a clear and structured way to technical and non‑technical stakeholders
• Support customer discussions, demos, and technical clarifications to build confidence in Vodafone’s AI capabilities
• Validate model performance, data quality, and technical compliance against defined acceptance criteria
• Identify and resolve technical issues related to data quality, scalability, latency, or model behavior
• Support solution readiness reviews prior to customer handover, ensuring alignment with agreed technical and business outcomes

• Excellent hands‑on experience with machine learning and deep learning algorithms
• Strong proficiency in advanced analytics, ML, deep learning, and Generative AI (GenAI)
• Minimum 4–6 years of experience in data science, AI, and analytics roles
• Proven experience in building and deploying AI/ML models in production environments
• Good proficiency in data visualization tools (Power BI, Tableau) to communicate insights effectively
• Solid knowledge of relational databases (e.g., MySQL) for efficient data storage and querying
• Experience with big data analytics frameworks, including PySpark and Spark clusters
• Strong skills in data mining, feature engineering, and time‑series forecasting
• Good working knowledge of Linux operating systems
• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field
• 4–6 years of hands‑on experience developing and deploying AI/ML models in production environments
• Strong proficiency in ML libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit‑learn)
• Solid experience in Generative AI and NLP, including working with large language models and frameworks (e.g., Hugging Face, LangChain, OpenAI APIs, agent‑based frameworks)
• Experience with big data processing and distributed computing (e.g., Apache Spark or equivalent)
• Practical experience deploying AI and data solutions on cloud platforms (e.g., AWS, Azure, GCP) and/or on‑prem environments
• Working knowledge of MLOps tools and practices for CI/CD, monitoring, and model lifecycle management

Exposure to full‑stack web development is considered a plus