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. 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 commercial Business Unit on impactful use cases and thus contributing to business strategy and roadmap.

Key Accountabilities and Activities:

1-Advanced Analytics & Data Modelling (To All Commercial Functions)
Understand business requirement for Consumer Business Unit and implement data mining models to do value addition on top of existing analytics
End to end AI/ML based model building & advance analytics use cases in data science tool (e.g. SAS /R/Python) and SQL with feature extraction/data source identification and collection, pre-processing of data, training, scoring, and actionable insight extraction.
Act as the custodian of advanced analytics assets within the organization and utilizes the power of advanced analytics tools, techniques, practices and data (both internal and external).
Working as part of shared function across organization on use cases to support product growth, cost optimization, customer engagement etc.
Feature engineering and insights through statistical measures/algorithms/graphs/info graphics.
Analyze large amounts of information to discover trends and patterns
Aid in data driven decision making by enabling key analytical insights derived from multidimensional data from varied sources.
Support to enhance business processes for data monetization, commercialization whilst offering valuable insights to improve customer experience across touch points.
Build predictive AA models using AI/ML based algorithms. This shall include training, scoring and end to end automation.
Combine models through ensemble modeling
Presenting results of the models in a business friendly format
Visualization of key business insights and data using advanced techniques and tools
Continuous support to use case owner departments by optimizing the models via optimization and self-learning
Aggressive tracking of results and utilization of leads.
Manage the Data Science Operational Framework
Assess the effectiveness and accuracy of new data sources and data gathering techniques.
Develop processes and tools to monitor and analyze model performance and data accuracy.
Propose solutions and strategies to business challenges using key insights from AA models.
1-Use Case Formulation & Insights exploitation (Marketing / Sales Team Specific - B2B / B2C )
Work closely with marketing team and provide segment specific recommendations and insights to improve targeting efficiencies and yield.
Work in close coordination with CVM team and develop cross functional shared business use cases.
Develop strategic use case models such as customer 360 , LTV , Survival models, segmentations ...
Develop use cases for sales and distribution using spatial data / NW data and competition customer data.
Harvest social data for targeted communication, customer sentiments, identifying behavioural and interest based communities digital targeting.
1-Data ecosystem Development & Maintenance
(Technology)Closely work with Technology BI team on matters related to Data, platforms and software.
Identify and integrate new data sources to Big data platform.
Governance and access rights on AA platforms and data.
Integration and sharing of AA model outputs with various customer touchpoints and IT systems.
Inputs for Platform Performance and vendor selection
Support planning activities for Analytics capabilities
1-Internal & External Organizational Collaboration
Collaborate and aligned with Group AA team for strategic initiatives and policies.
With Group:
Engage with peers in the group and opcos and share knowledge and models.
Ensure AA models and technologies are well communicated, understood and adopted by business units and users in a timely manner.
Implement Group team’s recommendations and fulfil the requirements as per their guidelines.
Necessary knowledge and Experience to be able to do the job
Required minimum Eight (8) years of years of experience in AI/ML base advanced analytics and development experience using a leading data science tool.
At least Five (5) years with a telecom operator in similar capacity while working with Technology teams.
Excellent understanding of Telco. Commercial practices.
Expertise in data Science Methodology and processes.
Ability to translate business requirements into AA model specs.
Expertise in:
Statistical & Analytical skills.
AI / ML techniques & Algorithms.
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: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
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).
Tools & Technology
Python, R programming, and other Data Science related Programming languages
Tensor flow, Keras, spark
Hadoop, Teradata
Exposure using SAS , MATLAB,SPSS, Alteryx
Visualization using Qliksense, Tableau
MS Office

Qualifications:

Bachelor’s Degree from a reputed Educational Institute in in any of the following:
Computer Science
Engineering
Information Technology / Information System
Data Science / AI
MBA is an added advantage
Certification in leading data science tools

Other Information:

Job specific technical Skills
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.

Industry/Domain

Advanced Analytics / Mobile Telecom

Ooredoo

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