دانشمند داده

Job Description

Missions:

• To deliver keen and smart solutions via the moving dynamics of the system.
• To provide full and comprehensive data-driven solutions to the most pressing challenges of marketing and business to efficiently solve complicated business problems.

Responsibilities:

• To liaise with various marketing teams in order to induct them in data science concepts in order to address business requirements.
• To collaborate with business partners to specify use cases and work with end users for agile use case improvement.
• To collaborate with subject matter experts to select the relevant sources of information and translate the business requirements into a data-scientific project.
• To collaborate with Data Governance personnel to ensure that the correct standards are aligned with the Data pipeline development process.
• To build high-performance algorithms, prototypes, predictive models, and proof of concepts to review data from various perspectives and generate insightful reports
• To refine and tune data models to be able to respond to various homogenous data structures.
• To exploit multiple new/existing algorithms for processing data to generate real business value
• To discover insights and identify opportunities using statistical, algorithmic, machine Learning/Mining, and visualization techniques.
• To propose and design data-efficient models that are smartly developed in accordance with the quality of existing data.
• To process huge volumes of data collected from multiple internal and external sources.
• To employ sophisticated analytics programs, machine learning, and statistical methods to do both predictive and prescriptive modeling.
• To search and propose various ways in order to compensate for unavailable required data by doing scientific experiments.
• To apply advanced knowledge and draw conclusions in the analysis/research around opportunities/strategies, sales retention opportunities, and market demographics utilizing internal/external market intelligence.
• To develop models and frames of business scenarios that are meaningful and which affect critical business processes and/or decisions.
• To deploy scientific approaches in order to validate built models by quantifying the resulting accuracy.
• To analyze big data in order to build data-driven business insights and high-impact data models to generate significant business value.
• To contribute to conducting undirected research and frame open-ended MTNIrancell business questions.