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Head of Predictive Modelling & Data Science Section
Head of Predictive Modelling & Data Science Section
The Head of Predictive Modelling & Data Science Section will manage the bank's enterprise Modeling & Data mining function, addressing complex analytical modeling and data mining requests from business units. This role involves researching new data mining methods, planning implementations, and communicating findings, leveraging strong understanding of banking strategy, data architecture, and analytical applications.
About the role
JOB PURPOSE / ROLE:
To manage the enterprise Modeling & Data mining function for the bank as a component of the EBIA mandate in order to ensure that complex analytical modeling and Data mining requests coming from the business units are addressed using data mining methodologies and tools. And to manage, analyze and summarize the information in innovative ways.
The Head of Predictive Modelling & Data Science will be responsible to research new and sophisticated data mining methods and applications; plan and develop implementations and communicate the findings.
- Understanding of the bank’s strategy, objectives, products and services
- Understanding in the market trends and competitors’ awareness
- Understanding of analytical applications development and usage to support business decision making
- In depth knowledge in the architecture required for data management
- Knowledge of the operations, products and services of banks and financial institutions
- In depth knowledge in Oracle EDW data model for Banking and financial institutions
- In depth understanding of Enterprise Business Intelligence and Reporting principles and key components
- He must have the knowledge of Analytics, data mining techniques and tools. Also, he should have high experience in information and Data base management as well as the business and domain knowledge.
- Analytics and Data mining: He must know the difference between specific statistical, analytical techniques and optimize the usage of different types of predictive models.
- Business knowledge: understand the business direction, processes, rules, requirements and deficiencies.
- Business-area respect: Need to promote the usage of data mining techniques through the communication of Best practices and success stories in similar organizations.
- Technology: Strong understanding of relational database structures, theories, principles and practices. Experience and facility in using Statistical and data mining tools as well as reporting and Dashboard applications.
QUALIFICATIONS & EXPERIENCE:
Minimum Qualifications:
- Master's degree in statistics, computational linguistics, computer science or a related quantitative methods plus
Minimum Experience:
- 6-8 years relevant experience in data analysis or analytical applications in a financial institutions including at least 3 years in positions of progressively increasing managerial responsibilities
- 8 years of data analysis and reporting experiences
- 5 years of Banking industry including knowledge CRM, marketing and strategy support
Language:
English: Advance