RAKBANKPrincipal Data Scientist
RAKBANK is hiring a Principal Data Scientist for a remote role open to applicants in United Arab Emirates. Level rates it ; you can apply on Level.
AI in this role
Lead the development and deployment of advanced machine learning solutions, propensity models, and MLOps practices to power personalized customer decisioning.
Job Purpose:
To lead the development and deployment of advanced machine learning solutions that power personalized customer decisioning, while driving best‑in‑class modeling, MLOps, and data engineering practices. This role combines hands‑on technical expertise with leadership to deliver scalable models, robust pipelines, and high‑impact insights across the organization.
What You Will Bring:
Modeling Expertise:
- Advanced experience in building and deploying propensity models for cross-sell and upsell.
- Deep understanding of Next Best Action / Next Best Offer engines.
- Strong grasp of supervised learning, uplift modeling, and causal inference.
Programming & Engineering:
- Expert-level coding in Python (mandatory); familiarity with R or Scala is a plus.
- Experience with distributed computing (Spark, Dask, Ray).
- Proficient in writing production-grade ML pipelines using tools like Airflow, MLflow, or Kubeflow.
- Strong understanding of software engineering best practices: version control, CI/CD, testing.
Data Infrastructure:
- Experience with cloud platforms (AWS/GCP/Azure) and data warehouses (Snowflake, BigQuery, Redshift).
- Strong SQL skills; ability to optimize queries and manage large datasets.
MLOps & Deployment:
- Experience deploying models to production via APIs or streaming systems (Kafka, Flink).
- Proficient in model versioning, experiment tracking, and deployment using MLflow, SageMaker, or Vertex AI.
Monitoring & Observability:
- Ability to set up model monitoring, drift detection, and alerting systems using Prometheus, Grafana, Evidently, or custom dashboards.
- Experience with logging frameworks and performance profiling for ML services.
GenAI (Preferred):
- Experience with LLMs, embeddings, prompt engineering, and vector databases (e.g., FAISS, Pinecone).
- Ability to integrate GenAI into decisioning systems or customer-facing products.
Leadership & Collaboration:
- Ability to lead senior data scientists while remaining hands-on.
- Comfortable working with product managers, engineers, and business stakeholders.
What You We are Looking For:
- Bachelor's degree in a relevant field including Econometrics,Acturial Science.Maths/Statistics, Computer Science etc,
- 10 years' experience in a senior data scientist position
- Modelling experience including knowledge of Cloud and GenAI
- Strong Analytics experience in the bank sector is an advantage
What’s In It for You
- Pay for performance culture (Competitive and performance-linked compensation)
- Diverse workforce and inclusive culture
- Career development and growth opportunities by design
- Work with the best minds in the field
- Get opportunities to bring your whole self to the organization and perform to your best.
How we rate this
Principal Data Scientist at RAKBANK rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where mlops was part of your work. What did you do?
- Tell me about a project where data science was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Prompt engineering, ML Ops, Machine learning, MLOps, and Data Science. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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