Data Science Associate: ML & Analytics for Banking

QNB Group; Doha; On-site; QAR 120,000 - 180,000; Full time

Job summary

QNB Group is seeking an Associate, Data Science to support data science initiatives across the bank. You will build and deploy machine learning models, conduct exploratory data analysis, and generate data-driven insights to solve business problems.

Collaboration with business units will shape requirements and scalable data science assets aligned with QNB’s goals. You will work on KPI development, data analytics solutions, and production-ready pipelines while supporting model testing, deployment,

Qualifications

• Bachelor degree in data science, computer science, mathematics, engineering or related field.
• Familiarity with machine learning techniques, data wrangling, and model evaluation practices.
• High level knowledge in Python, R and Jupiter notebooks is desirable.

Responsibilities

• Shareholder & Financial: Support KPI development and tracking for data science initiatives.
• Customer: Prepare clear, concise reports or dashboards for business users and ensure timely delivery.
• Internal: Develop ML models and contribute to AI/ML pipelines and scalable assets.
• Learning & Knowledge: Stay updated on trends, participate in trainings, and share progress within the team.

Skills

Machine learning

Data wrangling

Data analysis

Python

R

Jupiter notebooks

Education

Bachelor Degree in data science, Computer Science, Mathematics, Engineering, or related field

Tools

Jupiter notebooks

Job description

QNB Group is seeking an Associate, Data Science to support data science initiatives across the bank. You will build and deploy machine learning models, conduct exploratory data analysis, and generate data-driven insights to solve business problems.

Collaboration with business units will shape requirements and scalable data science assets aligned with QNB’s goals. You will work on KPI development, data analytics solutions, and production-ready pipelines while supporting model testing, deployment,