Company: Alinma Bank | مصرف الإنماء
Location: Riyadh Saudi Arabia
Employment Type: Full-time
Description:
Summary of role:
The role of the Head of Retail Analytics is to build and manage the internal analytics unit, and capabilities. This role requires a deep understanding of banking financial data structures, familiarity with data programming languages and data science techniques, digital banking experience, and managerial experience.
Responsibilities:
-Lead the retail analytics stream within the analytics unit and ensure continuous development of the team’s capability.
– Manage the reporting responsibilities and build the needed internal dashboards.
-Develop custom data models and algorithms to apply to data sets.
-Use advanced techniques in predictive modeling to increase and optimize customer experiences, sales maximization, revenue generation, ad targeting, and other business outcomes.
-Develop company A/B testing framework and test model quality.
-Coordinate with different functional teams to implement models and monitor outcomes.
-Develop processes and tools to monitor and… analyze model performance and data accuracy.
-Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques, and business strategies.
-Assess the effectiveness and accuracy.
Requirements:
-Intellectual curiosity, along with excellent problem-solving and quantitative skills, including the ability to disaggregate issues, identify root causes and recommend solutions
-Communication skills and ability to communicate analytical and technical content in an easy to understand way.
Experience and qualification
-Bachelor’s degree in a quantitative field like Computer Science, Engineering, Statistics, Mathematics or a related field required.
– Banking industry experience is a must.
-+5 years of hands-on mathematical modeling experience in a business environment
-Proven experience in working with large datasets and relational databases (SQL)
-Advanced knowledge of statistical and data mining techniques (regression, decision trees, clustering, neural networks, etc.)
-Knowledge of additional programming languages is a plus (Python, C++, Java) of new data sources and data-gathering techniques
Source: LinkedIn
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