Data Science and Analytics Lead

Titc; Dubai; On-site; AED 250,000 - 350,000; Full time

Job summary

A leading technology company in Dubai is seeking a Data Science and Analytics Lead to enhance credit risk modeling and operational efficiency. In this role, you will drive data science strategies, build AI-powered credit scoring models, and collaborate with cross-functional teams. The ideal candidate has a strong background in data science, leadership skills, and a Bachelor's degree in a quantitative field. This position offers a unique opportunity to be at the forefront of digital banking innovation in high-growth markets.

Qualifications

• Strong background in data science and AI with experience in credit risk modelling.
• Deep understanding of AI governance, model transparency, and regulatory compliance.
• Hands-on experience with MLOps and automated monitoring solutions.

Responsibilities

• Drive data science strategy for business growth and market expansion.
• Build and deploy AI-powered credit scoring models.
• Collaborate with engineering to expand data science capabilities.

Skills

Data science

Machine learning

AI governance

Leadership

Analytical mindset

Education

Bachelor's degree in a quantitative field

Tools

AWS

GCP

Azure

Job description

We represent a technology player whose digital banking platform is transforming financial services in emerging markets making a real impact by embedding credit and savings products into the digital channels people use every day. Their datadriven technology powers MNOs, fintechs, and banks enabling them to scale fast and drive financial inclusion for millions. For those looking to work on cuttingedge financial tech with realworld impact this is the opportunity for you. With rapid growth industry recognition and a team that thrives on innovation this is a chance to shape the future of finance in highgrowth markets across Africa.

Job Description: The Data Science and Analytics Lead will enhance their credit risk modelling predictive analytics and operational efficiency. Improve multisource data integration strengthening model governance automating data processes and scaling our infrastructure for faster decisionmaking and market expansion. The Data Science and Analytics Lead will drive datadriven insights refine risk models and build scalable solutions that optimize lending decisions and business growth.

Your daily adventures include:

Strategic Leadership & Business Impact

• Drive the development and of the data science strategy to support business growth embedded finance and new market expansion
• Leverage AI and behavioral science insights to enhance credit performance customer engagement and savings adoption.
• Partner with product risk and engineering teams to integrate data science into decisionmaking and operational processes

Model Development & AI Governance

• Build refine and deploy AIpowered credit scoring models ensuring high performance fairness and explainability.
• Lead experimentation and A/B testing initiatives to enhance underwriting portfolio management and product innovation.

Data Infrastructure & Scalability

• Collaborate with Engineering to expand data science capabilities to support multiple markets optimizing for scalability and adaptability
• Ensure data integrity security and compliance across all data science initiatives

Team Leadership & Development

• Drive best practices in model development MLOps and responsible AI
• Promote crossfunctional collaboration to maximize the value of data science across the organization.

Requirements and What it takes to succeed

• Strong background in data science machine learning and AI with experience in credit risk modelling and financial services
• Deep understanding of AI governance model transparency and regulatory compliance in financial services
• Handson experience with MLOps model deployment and automated monitoring solutions
• Strong analytical mindset with a proven ability to drive business impact through data science
• Excellent leadership skills with the ability to mentor and build highperforming teams
• Bachelors degree in a quantitative field such as Statistics Mathematics Physics Computer Science Data Science Engineering Economics Financial Engineering Actuarial Science or a related discipline
• Experience in fintech digital lending or embedded finance is preferred
• Exposure to cloud platforms such as AWS GCP or Azure for data engineering and machine learning is beneficial
• Familiarity with graph analytics network science or behavioral data modelling is beneficial
• Knowledge of causal inference techniques and advanced experimentation methodologies is beneficial
• Prior experience in expanding data science functions into new markets is beneficial