Senior Specialist Data Science

About the Company

Ooredoo is a major telecommunications group with operations across 10 countries and a customer base of more than 138 million. In Qatar, the business has around 1,600 employees and aims to be the preferred provider of communications services. This position offers the chance to contribute to that mission.

Role Summary

The Senior Specialist Data Science role is focused on strengthening the AI function by partnering with stakeholders across B2B, B2C, Technology, Finance and other teams to identify and deliver high-impact AI/ML and generative AI use cases. The work supports business strategy, digital expansion, and the wider data and AI roadmap.

The role is centered on converting customer and commercial requirements into scalable machine learning, generative AI, and data science solutions. These solutions will support key business areas such as customer value management, marketing, digital sales, and customer care.

Business Context

Ooredoo follows a strong data-led operating model. As the business continues to evolve, there is increasing emphasis on applying AI and ML in everyday operations to improve value creation, efficiency, and diversification.

The AI Hub is responsible for defining and executing the data and AI roadmap, business plan, and strategy. The organization is also building cloud-based capabilities on GCP for data platform, analytics, and ML workloads, while Azure supports generative AI and agentic AI workloads.

Key Responsibilities

• Interpret telecom business needs across B2C and B2B and develop AI/ML models that generate measurable business value.
• Take ownership of the full AI/ML lifecycle, from defining the problem and exploring data to feature engineering, training, validation, deployment, monitoring, and ongoing refinement.
• Deliver customer value management solutions such as churn prevention, customer lifetime value modeling, propensity scoring for upsell and cross-sell, and next-best-offer/next-best-action frameworks.
• Enable hyper-personalized and real-time decisioning through recommendation engines, decision logic, and event-driven scoring for always-on campaigns and contextual offers.
• Support marketing and digital sales performance by building audience segmentation, campaign optimization, attribution and uplift analysis, personalized messaging, and funnel conversion insights.
• Create call center optimization solutions including call volume forecasting, workforce planning inputs, routing and prioritization analytics, and AI-assisted service workflows.
• Design conversational AI and generative AI solutions such as virtual assistants, agent support tools, summarization, and knowledge retrieval to improve customer experience and efficiency while staying within governance requirements.
• Work confidently with PL/SQL for feature creation, data preparation, model training, scoring, and insight generation on platforms such as Teradata and Oracle.
• Translate analytical findings into clear, business-ready visuals, including statistical outputs, graphs, and infographics for stakeholders and leadership teams.
• Track model performance and business impact, and follow up with use case owners to ensure adoption and realization of outcomes.
• Apply Responsible AI principles, including governance, documentation, privacy-by-design, bias and robustness testing, explainability where needed, and secure handling of customer information.
• Improve the Data Science Operational Framework by defining standards for reusable code, model registries, version control, and release management with Technology teams.
• Collaborate across the organization on initiatives that drive product growth, cost efficiency, customer engagement, and better customer experience.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a similar discipline.
• At least 10 years of experience in a comparable data science or AI/ML role.
• Practical experience with advanced analytics and hands-on work on data science platforms, especially Dataiku, using Python and R.
• Strong background in predictive modeling for telecom customer analytics, including churn, propensity, customer lifetime value, segmentation, recommendation/decisioning systems, and time-series forecasting.
• Experience delivering hyper-personalization and next-best-offer/next-best-action solutions in marketing and digital sales environments.
• Working knowledge of GenAI/LLM methods such as prompt engineering, retrieval-augmented generation, evaluation approaches, and guardrails, with hands-on use of Gemini and/or Azure AI for automation and customer experience.
• Strong SQL and PL/SQL capability for advanced feature extraction using enterprise-scale data platforms such as Teradata, Oracle, and BigQuery.
• Familiarity with MLOps practices including version control, pipeline orchestration, model registries, CI/CD deployment patterns, monitoring, and lifecycle management within Dataiku and with Technology teams.
• Understanding of Responsible AI principles, especially privacy, security, and bias mitigation for models and automated decisions.
• Sound knowledge of telecommunications commercial processes and customer journeys, with the ability to work across Product, Marketing, Sales, Digital, and Technology teams.

Additional Information

This is a full-time onsite position based in Doha, Qatar. No salary, number of openings, start date, or application deadline was specified in the source information.

The role is intended to support a shared organizational function across multiple business areas and is expected to contribute to growth, optimization, engagement, and customer experience improvements.

No internship duration applies to this position.