أدخل المسمى الوظيفي أو الكلمة الرئيسية

Data Science and Analytics Lead

Titc

موقع الوظيفة:

دبي - الإمارات

الراتب شهرياً: لم يتم تقديمه من قبل صاحب العمل

تم النشر: 12 يونيو 2026 (نُشرت منذ أكثر من 30 يومًا)

آخر موعد للتقديم: 10 سبتمبر 2026

عدد الوظائف الشاغرة: 1 عدد الوظائف الشاغرة

سجل للتقديم

ملخص الوظيفة

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

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