Welcome to our talent management solutions. We are a bright young company committed towards bridging the gap between the right talent and right opportunities at companies. Our philosophy is to always keep people first. We offer bespoke, highly tailored recruitment solutions to our clients; global, multi-national organisations and predominant local businesses, as well as government entities across the UAE and wider GCC market.

We recruit across all industry sectors and we pride ourselves on developing sustainable and long-standing relationships, with our clients and candidates. Our approach is to identify what you want to achieve and then help you deliver it as rapidly as possible. How do we do this? By working alongside you as a partner, not just as a supplier, we’ll be there from the start to finish. We call it The Talent Arabia Way, in our view, it’s simply a better way of working.

Talent Arabia

We have an urgent requirement for Data Scientist - Banking Risk Models, MLOps &amp; AWS SageMaker&nbsp; in banking domain is required&nbsp;for our banking clients in Abu Dhabi ,UAE
&nbsp;
Strong ML Engineering &amp; MLOps expertise.--MustExtensive AWS SageMaker experience--Must.Experience with Risk, SME, Retail Banking, Propensity, and Churn Models--MustCapable of taking ML solutions from experimentation to enterprise-scale production deployment--MustBanking Domain --Must 
Key Responsibilities
Machine Learning &amp; Model Development
<ul>
<li>Design, develop, validate, and deploy advanced machine learning models for banking use cases.</li>
<li>Build and enhance:</li>
<ul>
<li>Credit Risk Models</li>
<li>Business Banking Models</li>
<li>SME (Small &amp; Medium Enterprise) Models</li>
<li>Retail Banking Models</li>
<li>Propensity Models</li>
<li>Customer Churn Prediction Models</li>
</ul>
<li>Implement feature engineering, model selection, hyperparameter tuning, and performance evaluation.</li>
<li>Translate business requirements into scalable AI/ML solutions.</li>
</ul>
ML Engineering &amp; MLOps
<ul>
<li>Build end-to-end ML pipelines from data ingestion to production deployment.</li>
<li>Implement MLOps best practices including CI/CD, model versioning, experiment tracking, model monitoring, and automated retraining.</li>
<li>Develop scalable and reusable ML frameworks for enterprise adoption.</li>
<li>Monitor model performance and address model drift, bias, and data quality issues.</li>
</ul>
AWS &amp; SageMaker
<ul>
<li>Design and deploy ML solutions using AWS ecosystem.</li>
<li>Build and manage machine learning workflows using:</li>
<ul>
<li>AWS SageMaker</li>
<li>S3</li>
<li>Lambda</li>
<li>Glue</li>
<li>Redshift</li>
<li>RDS</li>
<li>Step Functions</li>
<li>IAM</li>
<li>CloudWatch</li>
</ul>
<li>Optimize cloud infrastructure for performance, scalability, and cost efficiency.</li>
</ul>
Banking Domain &amp; Analytics
<ul>
<li>Work with large-scale banking and financial datasets.</li>
<li>Partner with Risk, Compliance, Fraud, Business Banking, Retail Banking, and Analytics teams.</li>
<li>Ensure adherence to banking regulations, data governance, model risk management, and data security standards.</li>
<li>Deliver actionable insights and predictive solutions supporting business growth and risk mitigation.</li>
</ul>
Required QualificationsExperience
<ul>
<li>Minimum 7+ years of experience in Data Science, Machine Learning Engineering, or Advanced Analytics.</li>
<li>4+ years of hands-on experience in ML Engineering and MLOps.</li>
<li>Proven experience in Banking or Financial Services domain is mandatory.</li>
</ul>
Technical Skills
<ul>
<li>Strong expertise in:</li>
<ul>
<li>Python</li>
<li>Machine Learning</li>
<li>ML Engineering</li>
<li>MLOps</li>
<li>AWS SageMaker</li>
<li>AWS Cloud Services</li>
<li>SQL</li>
<li>PySpark</li>
</ul>
<li>Experience with:</li>
<ul>
<li>Model Deployment &amp; Monitoring</li>
<li>CI/CD Pipelines</li>
<li>Docker</li>
<li>Kubernetes (preferred)</li>
<li>Git</li>
<li>Airflow</li>
<li>Feature Stores</li>
<li>Experiment Tracking Tools</li>
</ul>
</ul>
Banking Model Experience (Mandatory)Candidate should have hands-on experience developing or managing at least several of the following:
<ul>
<li>Risk Models</li>
<li>Credit Scoring Models</li>
<li>Business Banking Models</li>
<li>SME Models</li>
<li>Retail Banking Models</li>
<li>Propensity Models</li>
<li>Churn Prediction Models</li>
<li>Customer Segmentation Models</li>
</ul>
edshift).
<ul>
<li>Education: Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related quantitative field.</li>
</ul>
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