Senior Data Scientist

Role Overview:

We are seeking a highly skilled and motivated Senior Data Scientist with deep expertise in Generative AI, Machine Learning, Deep Learning, and advanced Data Analytics. The ideal candidate will have hands-on experience in building, deploying, and maintaining end-to-end ML solutions at scale, preferably within the Telecom domain.

You will be part of our AI & Data Science team, working on high-impact projects ranging from customer analytics, network intelligence, churn prediction, to generative AI applications in telco automation and customer experience.

Key Responsibilities:

• Design, develop, and deploy advanced machine learning and deep learning models for Telco use cases such as:
• Network optimization
• Customer churn prediction
• Usage pattern modeling
• Fraud detection
• GenAI applications (e.g., personalized recommendations, customer service automation)
• Lead the design and implementation of Generative AI solutions (LLMs, transformers, text-to-text/image models) using tools like OpenAI, Hugging Face, LangChain, etc.
• Collaborate with cross-functional teams including network, marketing, IT, and business to define AI-driven solutions.
• Perform exploratory data analysis, feature engineering, model selection, and evaluation using real-world telecom datasets (structured and unstructured).
• Drive end-to-end ML solution deployment into production (CI/CD pipelines, model monitoring, scalability).
• Optimize model performance and latency in production, especially for real-time and edge applications.
• Evaluate and integrate new tools, platforms, and AI frameworks to advance the organization's data science capabilities.
• Provide technical mentorship to junior data scientists and data engineers.

Required Qualifications & Skills:

• 6-9 years of industry experience in Machine Learning, Deep Learning, CNNS, and Advanced Analytics.
• Strong hands-on experience with GenAI models and frameworks (e.g., GPT, BERT, Llama, LangChain, RAG pipelines).
• Proficiency in Python, and libraries such as scikit-learn, TensorFlow, PyTorch, Hugging Face Transformers, etc.