Sr Data Scientist

JOB ID:QT-SNB-08-364

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 clients 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, 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.

Disclaimer: This job posting and location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.