Senior Specialist Data Mining - Gadget Express

Job Summary

Role Purpose: Plays a senior role in the Data Mining team. Support delivery of Data mining and predictive analysis using data mining tools to support various business initiatives such as Retention Loyalty cross sell up sell

Key Accountabilities & Responsibilities:

• Oversee activities related to other teams within Business Intelligence Unit.
• Support other Business Intelligence team leaders.
• Build Intelligence using data mining features and tools to support various business initiatives such as Customer Retention Loyalty Cross sell Up Sell
• Support business with segmentation/clustering and target building activities with the help of data mining techniques
• Support business with targeting the right segments for Cross selling / Up Selling various offers products and services
• Build predictive models to support various business requirements
• Build relevant data mining models including churn crosssell/upsell clustering/segmentation value (including life time value) survival and time series models
• Enhance and optimize existing data mining models.
• Participate in implementation of relevant projects and tasks including prediction cycles clustering/segmentation exercises/cycles value and lifetime value crosssell/upsell survival time series and association rules related projects and activities.
• Initiate participate and oversee the creation of analytical infrastructure and associated analysis and reporting that includes weekly and monthly variables covering many aspects of customers including demographics usage social network revenue etc. Infrastructure would help answer different business questions including churn and retention and support multiple analytics and analytical activities.
• Oversee and participate in the enhancement of customer DNA to be actionable marketing database that includes data mining and non data mining vectors. DNA would enable churn retention loyalty segmentation and crosssell and upsell efforts in a segmented and targeted manner.
• Segment prepaid and postpaid customer bases by using new analytical infrastructure and data mining to generate a segmentation that would provide better insight and enhanced understanding of our customers.
• Manage the process of Data Mining standards.
• Support provision of daily weekly monthly and adhoc reports from the Data Warehouse.
• Ensure that MIS/Data Mining reports and queries are delivered within the Service Level Agreements set.
• Ensure the availability of desktop reporting query facilities support and training to end users.
• Research relevant new tools technologies methodologies best practices and ideas from different sources.
• Meet quality and performance KPI with supporting documents.
• Ensure that upper management is informed on all critical issues pertaining to the area responsible for.
• Provide reports make standard reports and tailor make them where necessary.
• Proactively take responsibility for self improvement by staying wellinformed of developments knowledge and innovations in relevant field of expertise.
• Other duties as directed by supervisor or other superiors.

Qualifications/Requirements:

• 34 years required years of experience based on progression ladder relevant IT/Data Warehouse analysis experience
• Strong Knowledge of the Telecom industry
• Strong knowledge of data warehousing relational databases SQL and reporting tools data mining techniques practices and methodologies
• Very good knowledge of different business areas and concepts including marketing sales finance strategy B2C B2B and CRM
• Ability to translate users requirements into MIS solutions
• Ability to operate in a diverse multicultural multinational work environment exhibiting appropriate sensitivities
• Good knowledge of MS Office applications like Excel Word etc.
• Excellent command of both written and verbal English Arabic would be an advantage
• Bachelor degree in Business or related discipline and appropriate registration with a recognised professional institute
• Strong Analytical skills
• Strong Project Management skills
• Strong Technical skills
• Management skills
• Strong interpersonal communication skills