Senior Manager, Data Scientist

VAC9396 - Senior Manager, Data Scientist

Field: Marketing

Contract Type: Full Time - Permanent

Location:

Closing Date: 31-Mar-2025

The Company

Ooredoo is an organisation on the move. Thanks to our dedicated employees, we continue to move closer towards our vision to be among the top 20 telecommunications companies in the world by 2020.

We are a dynamic global telecommunications player operating in 17 countries across the Middle East, North Africa (MENA) and Asia. We cover a population of more than half a billion people and serve more than 68 million customers.

In Kuwait, we employ approximately 1,000 talented people, all of whom are driving Ooredoo to be the number one choice for world-class communications services in Kuwait. In the face of intensifying competition, increasingly sophisticated technology and rising customer expectations, nothing is more important to our success than our team – and it's a team that you can be part of.

Ooredoo's future is bright, and you can be part of our ongoing success.

The Role

The role of the Data Scientist is to answer critical business questions around commercial functions, covering critical domains such as funnel optimization, customer retention, experience, business investment prioritization and opportunity identification, process automation. The Data Scientist will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes. The position will strengthen the advanced analytics capabilities by working closely with the commercial Business Unit on impactful use cases and thus contributing to business strategy and roadmap.

Ensuring the delivery of top-notch projects that yield substantial business value through various Data Science models such as Recommendation Engines, propensity models, and diverse segmentation techniques will also be your responsibility.

Furthermore, you'll play a pivotal role in driving initiatives related to data monetization strategies and identifying fresh business prospects by leveraging AI and data analytics to uncover potential revenue streams.

Key Accountabilities and Activities

1. Advanced Analytics & Data Modelling (To All Commercial Functions)
2. Understand business requirements for Consumer Business Unit and implement data Science models to add value on top of existing analytics.
3. Full stack AI/ML based model development & Lifecycle management.
4. DS Requirement analysis and Project management.
5. Statistical analysis and data visualization.
6. Develop and deploy various AI & DS models for revenue generation, cost reduction, and operational enhancement.
7. Collaborate with diverse teams to devise innovative data products for B2C and B2B markets.
8. Conduct comprehensive business analysis to provide insights for strategic decision-making.
9. Perform data pre-processing, feature engineering, and exploratory data analysis.
10. Build ETL pipelines to transform unstructured data into suitable formats.
11. Develop automated analytics solutions and APIs for data access and integration.
12. Deal with various data formats and apply techniques for data enrichment.
13. Integrate with big data ecosystems and optimize SQL queries.
14. Utilize tools like Airflow/ MLFlow for automated data pipelines and statistical methods for transformation.
15. Working as part of a shared function across the organization on use cases to support product growth, cost optimization, customer engagement, etc.
16. Feature engineering and insights through statistical measures/algorithms/graphs/info graphics.
17. Support to enhance business processes for data monetization, commercialization whilst offering valuable insights to improve customer experience across touchpoints.
18. Present results of the models in a business friendly format.
19. Visualization of key business insights and data using advanced techniques and tools.
20. Continuous support to use case owner departments by optimizing the models via optimization and self-learning.
21. Aggressive tracking of results and utilization of leads.
22. Manage the Data Science Operational Framework.
23. Assess the effectiveness and accuracy of new data sources and data gathering techniques.
24. Propose solutions and strategies to business challenges using key insights from AA models.
25. Work closely with the marketing team and provide segment-specific recommendations and insights to improve targeting efficiencies and yield.
26. Work in close coordination with the CVM team and develop cross-functional shared business use cases.
27. Develop strategic use case models such as customer 360, LTV, Survival models, segmentations.
28. Develop use cases for sales and distribution using spatial data/NW data and competition customer data.
29. Harvest social data for targeted communication, customer sentiments, identifying behavioral and interest-based communities digital targeting.

1. Data ecosystem Development & Maintenance (Technology)
2. Closely work with Technology BI team on matters related to Data, platforms and software.
3. Identify and integrate new data sources to Big data platform.
4. Governance and access rights on AA platforms and data.
5. Integration and sharing of AA model outputs with various customer touchpoints and IT systems.
6. Inputs for Platform Performance and vendor selection.
7. Support planning activities for Analytics capabilities.

1. Internal & External Organizational Collaboration (With The Group)
2. Collaborate and align with Group AA team for strategic initiatives and policies.
3. Engage with peers in the group and opcos and share knowledge and models.
4. Ensure AA models and technologies are well communicated, understood and adopted by business units and users in a timely manner.
5. Implement Group team's recommendations and fulfill the requirements as per their guidelines.

Qualifications

Bachelor's Degree from a reputed Educational Institute in any of the following:

• Computer Science
• DS / AI

MBA / MS/ MTech in DS / AI

Certification in leading data science tools is a plus.

Other Information

7-8 years of working experience in Data Science & AI.

Telecom data science experience is a big plus.

Expertise in data Science Methodology and processes.

Ability to translate business requirements into AA model specs.

• Statistical & Analytical skills.
• Expertise in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
• Experience analyzing data from 3rd party providers.
• Utilize tools like Airflow/ MLFlow for automated data pipelines and statistical methods for transformation.
• End-to-end AA model development lifecycle and automation.
• Ability to process large volumes of data using Big data.
• Advanced skills in Deep learning and data visualization.
• Strong Data Engineering skills (Structured and Unstructured).
• Strong SQL knowledge.
• Proficient in using MS Office tools.
• Business Presentation skills.

Tools & Technology:

• Python, R programming, and other Data Science related Programming languages.
• Statistical analysis and data Visualization.
• MS Office Strong analytical skills & project management Skills.
• Strong knowledge in Telco domain.
• Excellent presentation skills.
• Solution-oriented strategic/critical thinking, analytical skills, and the ability to be creative.

Note: you will be required to attach the following:
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