Data Scientist

Term: 12 months

Job Location: Riyadh and Jeddah, KSA

Project Scope: Develop Machine Learning Models leveraging Client data

Experience: 4+ years as a Data Scientist with hands-on experience in building Machine Learning models

Language: English proficiency. Arabic is an advantage.

Job Summary:

The Data Scientist will develop and validate predictive models using machine learning techniques. The role involves working with cross-functional teams to develop select use cases.

Roles and Responsibilities:

1. Develop and assist in the implementation of predictive models using machine learning techniques for various business needs, such as proactive retention, finding hidden affluent customers, customer segmentation, and identifying target segments for below-the-line marketing campaigns.
2. Lead end-to-end data science projects from data collection, cleaning, preprocessing, exploratory data analysis, feature engineering, model development, and validation.
3. Manage end-to-end data science projects, including problem definition.
4. Collaborate with Client internal stakeholders to define project scope, deliverables, and timelines.
5. Work closely with Data Engineering teams to establish data pipelines and infrastructure for efficient model development and deployment.
6. Communicate insights and recommendations to non-technical stakeholders through visualizations, presentations, and reports.
7. Actively and efficiently liaise with Mastercard Teams.
8. Monitor and conduct ongoing analysis of progress.
9. Provide comprehensive model documentation at the end of the project and plan project handover initiatives.

Requirements:

1. Over 4+ years of hands-on Data Science experience with a strong focus on predictive modeling and machine learning in a financial services or related industry.
2. Proven experience in managing end-to-end data science projects, from concept to deployment and maintenance. Should be capable of executing tasks independently once the scope is defined.
3. Strong stakeholder management skills.
4. Strong problem-solving skills with a focus on data-driven decision-making.
5. Ability to analyze large datasets, identify trends, and generate actionable insights.
6. Excellent verbal and written communication skills, with the ability to explain complex data science concepts to non-technical stakeholders.
7. Ability to work collaboratively in a team environment and influence stakeholders across various functions.
8. Masters or PhD in Data Science, Statistics, Mathematics, Computer Science, or a related field.
9. Proficiency in SAS, SAS EM, and Python.