Assistant Manager - FWA Data Science

Bupa Arabia; Jeddah; Sur place; SAR 180 000 - 240 000; Plein temps

Résumé du poste

Bupa Arabia seeks a data science professional to transform validated fraud analytics prototypes into robust detection models for healthcare. You will own model enhancement, feature engineering, calibration, validation, explainability, and continuous improvement across the lifecycle.

Collaborating with Actuarial, Claims Integrity, and FWA AI Engineering, you will ensure models stay effective against evolving fraud patterns after deployment and ready them for production in cloud environments.

Qualifications

• Bachelor's degree in a relevant field.
• Experience in health insurance, claims analytics, or financial crime analytics preferred.
• Strong Python/SQL/SAS skills with cloud analytics experience.

Responsabilités

• Model Industrialization Readiness: assess AI/ML prototypes and refine logic.
• Detection Model Development & Enhancement: retrain models and develop features.
• Model Validation & Performance Science: define metrics and validate outputs.
• Fraud Intelligence & Pattern Evolution: analyze outcomes and identify evolving fraud behaviours.
• Continuous Model Optimization: monitor deployed models and plan retraining.

Connaissances

Python

SQL

SAS

Machine Learning

Statistical Analysis

Feature Engineering

Model Validation

Fraud Analytics

Healthcare Analytics

NLP

GCP

Data Visualization

Cloud Analytics

Power BI

Stakeholder Management

Communication

Collaboration

Health Insurance

Formation

Bachelor's Degree in CS/DS/AI or related field

Outils

SAS FWA

Power BI

Description du poste

• Develop explainable detection methodologies.

Job Description

Role Purpose

FWA Data Science is responsible for transforming validated FWA analytical prototypes into robust, scalable, and measurable detection models ready for production implementation. The role owns model enhancement, feature engineering, calibration, validation, explainability, performance assessment, and continuous model improvement throughout the solution lifecycle.

Working closely with Actuarial, Claims Integrity, and FWA AI Engineering, the role ensures FWA detection models remain effective, relevant, and aligned with evolving fraud patterns after deployment.

Key Accountabilities

• 1- Model Industrialization Readiness;
  • Assess AI/ML prototypes received from Actuarial teams.
  • Refine model logic and improve statistical rigor.
  • Enhance feature engineering methodologies.
  • Validate and clarify prototype assumptions.
  • Develop explainable detection methodologies.
  • Support migration of approved analytical models into cloud-based solutions.
• 2- Detection Model Development & Enhancement;
  • Improve and retrain FWA models using new data and investigation outcomes.
  • Develop advanced fraud detection features.
  • Enhance anomaly detection models.
  • Build risk scoring methodologies.
  • Improve model precision and operational effectiveness.
• 3- Model Validation & Performance Science;
  • Define model success metrics.
  • monitor precision, recall, and business impact.
  • Perform false-positive and false-negative analysis after go-live
  • Validate model outputs with investigators.
  • Support production readiness reviews.
• 4- Fraud Intelligence & Pattern Evolution;
  • Analyze investigation outcomes.
  • Identify emerging fraud behaviors.
  • Design new detection features.
  • Recommend modifications to existing models.
  • Collaborate with FWA operations on evolving threats.
• 5- Continuous Model Optimization;
  • Monitor business effectiveness of deployed models.
  • Recommend retraining and recalibration activities.
  • Support periodic model reviews.
  • Maintain model documentation and governance artifacts.

Skills

• Python
• SQL
• SAS
• Machine Learning
• Statistical Analysis
• Feature Engineering
• Model Validation & Performance Analysis
• FWA / Fraud Analytics
• Healthcare Claims Analytics
• NLP & LLM Applications
• Google Cloud Platform (GCP)
• Cloud-Based Analytics Solutions
• SAS FWA
• Power BI / Data Visualization
• Problem Solving
• Stakeholder Management
• Communication & Presentation Skills
• Cross-Functional Collaboration
• Experience in health insurance, claims analytics, FWA, risk management, or financial crime analytics is preferred.
• Experience working with Google Cloud Platform (GCP) is preferred.
• Experience using SAS for statistical analysis and model assessment.

Education

Bachelor's Degree in Computer Science, Data Science, Artificial Intelligence, or a related field