The Principal Data Scientist role involves building and deploying advanced propensity models, leading a team of data scientists, and collaborating with various stakeholders. Candidates must have extensive experience in machine learning, cloud platforms, and data infrastructure, with a strong background in analytics.
Company Description
At RAKBANK, we are committed to nurturing a culture of innovation, growth, and excellence. We go beyond being a bank – we are a thriving community fueled by teamwork, advanced solutions, and unwavering standards of governance.
Join us and be a part of shaping the future of RAKBANK!
Job DescriptionModeling 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.
- Bachelor's degree in a rellevant field including Econometrics,Acturial Science.Maths/Statistics,Computer Science etc,
- Strong Analytics experience in the bank sector is an advantage
- 10 years experience in a senior data scientist position
- Modelling experience including knoledge of Cloud,ML and GenAI
Additional Information
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.
Top Skills
Airflow
AWS
Azure
BigQuery
Dask
Evidently
Flink
GCP
Grafana
Kafka
Kubeflow
Mlflow
Prometheus
Python
R
Ray
Redshift
Sagemaker
Scala
Snowflake
Spark
SQL
Vertex Ai
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