Job Description: 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.