About the Role / About the Job
The Staff Data Science will lead the development of AI/ML solutions that drive data-driven decision-making across customer engagement, marketing, retention, risk, and product functions. The role requires strong analytical expertise, hands-on experience with open-source technologies, and the ability to build interactive applications and deploy models in both batch and real-time environments. The candidate will ensure high-quality delivery, effective stakeholder communication, and adherence to best practices for reproducible, scalable data science.
Ready to apply for roles like this?
Unlock the company name and direct application link. Subscribers get instant access to fresh jobs across Dubai, Abu Dhabi and Riyadh, many with visa support.
Unlock employer & apply directly
What You Will Do:
- Work with the Data Science team to translate business problems into analytical use-cases with defined outcomes. Develop, implement, and test the most appropriate algorithms for given use-cases.
- Collaborate closely with Business Analysts for requirement gathering and understanding. Work with Data Engineers to build data pipelines and automate/productionize complex ML models to derive insights and recommendations.
- Maintain a strong conceptual understanding of machine learning algorithms including multi-variate regressions, classification algorithms, time series techniques, clustering, NLP, image processing, and optimization models.
- Ensure high coding standards and design standards to guarantee reproducibility.
- Drive innovation by enhancing existing solutions, designing new ones, and building collaboration and awareness in the bank’s analytics community.
- Work closely with various business units/stakeholders to identify and streamline AI-ML use-cases.
- Deliver end-to-end AI-ML models from development to deployment, including delivery planning, stakeholder communication, and ensuring efficient usage of the models by the business for improving decision touchpoints.
- Ensure high coding standards, peer-review, and transparency in work with the reporting line.
- Support ad-hoc requirements including MIS development, building, and analyzing SAS Data Models, and streamlining the reporting process through various reporting and analytical tools.
What We Are Looking For:
- Overall 7+ years of experience in analytics, data science, or similar functions.
- 3-4 years of experience in banking analytics.
- Python and SQL experience required.
- Experience with end-to-end ML model deployment.
- Proficiency in Machine Learning, Deep Learning, Time-Series, Optimization, and Customer Analytics.
Technical Skills:
- Strong coding skills using Python.
- Knowledge of Retail Banking Products.
- Deployment experience in various environments including databases, server/cloud environments (AWS, Azure), and APIs, ODBCs, and web apps.
- Excellent knowledge of Banking Functional Knowledge is a major plus.
- Good written and oral communication, as well as documentation skills, with the ability to communicate effectively with stakeholders.
- Expert-level proficiency in Python, with SAS/R/Spark as a plus.
