Senior Specialist Data Science

Ooredoo Group of Companies
من Indeed
الموقع: الدوحة • عبر Indeed - وظائف قطر
النوع: دوام كامل
نُشرت: 1970-01-01
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تفاصيل الوظيفة

About Us:

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-pers