Senior Specialist Data Science

Ooredoo is a dynamic global Telecommunications player operating in 10 countries serving more than 138 million customers. Ooredoo Qatar employs approximately 1,600 people driving Ooredoo to be the number one choice for world-class communications services in Qatar, and it is a team that you can be part of!

About the Business Unit:

Ooredoo places strong emphasis on a data-driven culture. In an ever-changing business landscape, there is increasing organizational focus on using AI/ML in day-to-day practice to create value, efficiency, and diversification.

The AI Hub division is responsible for putting in place and executing the data & AI roadmap, business plan, and strategy. Ooredoo is building a cloud platform-based solutions involving GCP that hosts the data platform and supports analytics and ML workloads, while Azure hosts GenAI and agentic AI workloads.

About the Role:

This role is responsible for strengthening the AI practice by working closely with the relevant stakeholders (B2B/C, Technology, Finance etc.) on impactful AI/ML and GenAI use cases to contribute to business strategy, digital growth and an evolving data & AI roadmap. The role will focus on translating customer and commercial needs into scalable ML/Gen AI/Data Science models and decisioning capabilities across business domains including customer value management (CVM), marketing, digital sales and customer care. For more details, please click here.

About You:

• 10 years’ experience in a similar role.

• Prior experience in data science and AI/ML-based advanced analytics, including hands-on development on leading data science platforms (Dataiku as the primary platform) using Python and R.

• Demonstrated expertise in predictive modelling for telecommunications (telco) customer analytics (e.g., churn prediction, propensity, customer lifetime value (CLV), as well as segmentation, recommendation/decisioning systems, and time-series forecasting.

• Experience implementing hyper-personalization and Next Best Offer/Action frameworks in marketing and digital sales contexts.

• Practical knowledge of GenAI/LLM solutions (e.g., prompt engineering, retrieval-augmented generation, evaluation methodologies, and model guardrails) and hands-on experience using Gemini and/or Azure AI for automation and customer-experience use cases,

• Strong command of SQL and PL/SQL for advanced feature extraction with large-scale data on enterprise data platforms (e.g., Teradata, Oracle, BigQuery)

• Familiarity with MLOps practices – such as version control, pipeline orchestration, model registry, CI/CD deployment patterns, monitoring, and lifecycle management – within Dataiku and in collaboration with Technology teams.

• Understanding of Responsible AI principles, including privacy, security, and bias mitigation for AI models and automated decisioning.

• Excellent understanding of telecommunications commercial practices and customer journeys, and the ability to work cross-functionally with Product, Marketing, Sales, Digital, Technology teams.