Data Scientist

Melon Digital Insurance; Dammam; Hybrid; SAR 180,000 - 300,000; Full time

Benefits offered by this job

ESOP

Flexible hybrid work

Career growth

Job summary

Melon Digital Insurance is seeking a Data Scientist to build and deploy machine learning and computer vision models powering motor insurance products. The role is based in the Eastern Region with hybrid work.

You will develop CV models for damage detection, severity estimation, and fraud checks, and build predictive models for claims triage, loss forecasting, pricing, and fraud detection. Strong Python, CV tooling, and production experience are essential.

Qualifications

• Proven experience delivering production ML models in insurance or related fields.
• Hands-on CV experience with image datasets, detection, segmentation or classification.
• Strong Python and data stack skills (pandas, NumPy, scikit-learn, SQL).
• Experience in productionizing models via APIs, containers, and cloud tooling.

Responsibilities

• Develop, train, and deploy computer vision models for motor use cases.
• Build predictive models for claims triage, pricing, and fraud detection.
• Design data pipelines for image/telematics/policy/claims data and QA workflows.
• Collaborate with claims, underwriting, and product teams to define data science problems.
• Monitor model performance in production and run experiments to validate impact.
• Collaborate with engineering to put models into production via APIs and cloud ML tooling.
• Translate model outputs into actionable insights for management.
• Prepare reports, dashboards, and analytics for leadership review.
• Document methodology and governance artefacts to meet regulatory and internal standards.

Skills

Python

Computer Vision

MLOps

SQL

Data Visualization

Arabic

English

Tools

PyTorch

TensorFlow

Pandas

NumPy

Scikit-learn

SQL

Docker

Git

Job description

Role Overview

As a Data Scientist, you will build and deploy machine learning and computer vision models that power our motor insurance products, from automated damage assessment to claims triage and risk pricing. Based at our Eastern Region office, you\'ll work closely with cross-functional teams in a HYBRID environment to turn data into production-grade capabilities, improve decision accuracy, and drive analytical excellence within our organization.

Responsibilities

• Develop, train, and deploy computer vision models for motor use cases such as vehicle damage detection, severity estimation, part identification, and image fraud checks.


• Build predictive models supporting claims triage, loss ratio forecasting, reserving, pricing, and fraud detection.


• Design and maintain data pipelines for image, telematics, policy, and claims datasets, including labelling workflows and dataset quality controls.


• Partner with claims, underwriting, and product teams to frame business problems as measurable data science problems.


• Evaluate model performance in production, monitor for drift, and run experiments and A/B tests to validate impact.


• Work with engineering to productionize models through APIs, containerized services, and cloud ML tooling.


• Translate model outputs into clear insights and recommendations for business and management stakeholders.


• Prepare detailed reports, dashboards, and analytics for management review.


• Document methodology, assumptions, and model governance artefacts in line with regulatory and internal standards.

Must Have Requirements

• Proven experience as a Data Scientist delivering models into production, not only research or proof-of-concept work.


• Hands-on computer vision experience, including deep learning frameworks such as PyTorch or TensorFlow and practical work with image datasets, detection, segmentation, or classification.


• Experience in the insurance sector, with a solid understanding of claims, underwriting, or pricing data.


• Demonstrated motor or automotive related project experience, for example vehicle damage assessment, telematics, driver behaviour, repair cost estimation, or accident analysis.


• Strong Python skills and proficiency with the standard data stack, including pandas, NumPy, scikit-learn, and SQL.


• Strong analytical, problem-solving, and statistical reasoning skills.


• Outstanding communication abilities, including the ability to explain technical work to non-technical stakeholders.

Nice To Have Requirements

• Experience with cloud ML platforms on GCP or Azure, including Vertex AI or Azure ML.


• Familiarity with MLOps practices, model monitoring, versioning, and CI/CD for models.


• Experience with vision-language models, OCR, or document intelligence for claims processing.


• Exposure to model governance, explainability, and regulatory expectations for AI in insurance.


• Background in geospatial data, telematics, or IoT sensor data.


• Arabic and English fluency.

Perks And Benefits

• Employee Stock Ownership Plan (ESOP).


• Flexible hybrid work arrangements.


• Opportunities for career growth and professional development.


• Collaborative, innovative work culture.