Senior Data Scientist - 6 To 9 years - WFO - F2F Interview

Role & responsibilities

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 client's data science capabilities. 
• Provide technical mentorship to junior data scientists and data engineers. 

Required Qualifications & Skills:

• 69 years of industry experience in Machine Learning, Deep Learning, CNN’S, 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. 
• Experience in end-to-end model lifecycle management, from data preprocessing to production deployment (MLOps). 
• Familiarity with cloud platforms like AWS, GCP, or Azure; and ML deployment tools (Docker, Kubernetes, MLflow, FastAPI, etc.). 
• Strong understanding of SQL, big data tools (Spark, Hive), and data pipelines. 
• Excellent problem-solving skills with a strong analytical mindset and business acumen. 
• Prior experience working on Telecom datasets or use cases is a strong plus. 

Preferred Skills:

• Experience with vector databases, embeddings, and retrieval-augmented generation (RAG) pipelines. 
• Exposure to real-time ML inference and streaming data platforms (Kafka, Flink). 
• Knowledge of network analytics, geo-spatial modeling, or customer behavior modeling in a Telco environment. 
• Experience mentoring teams or leading small AI/ML projects.