AI/ML Scientist

Skills

Design develop and deploy AI/ML models to solve critical business problems such as risk modeling fraud detection predictive analytics and customer segmentation. Work with large datasets from various sources to extract meaningful insights and patterns related to insurance operations (e.g. underwriting claims and customer behavior). Develop and optimize features for AI/ML models to improve prediction accuracy and performance in insurance use cases. Work with business teams such as claims actuarial and underwriting departments to understand their challenges and identify AI/ML solutions. Monitor the performance of models in production update and retrain them as necessary to ensure continued accuracy and effectiveness. Collaborate with data engineers to build scalable and efficient data pipelines for model training and inference. Stay up to date with the latest advancements in AI/ML technologies and explore their application to insurance-specific use cases. Document model development processes assumptions and outcomes; create visualizations and reports for stakeholders.

Description

We are seeking an experienced AI/ML Scientist or Data Scientist with a strong background in the insurance domain. The ideal candidate will leverage machine learning (ML), artificial intelligence (AI), and data science to drive innovation in underwriting, claims processing, fraud detection, and customer experience within the insurance sector. You will work closely with cross-functional teams, including actuarial, claims, underwriting, and IT, to develop data-driven solutions that improve efficiency and decision-making processes.

Responsibilities

• Proficient in programming languages like Python, R, or Scala.
• Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Strong knowledge of data querying languages (SQL) and big data technologies (Hadoop, Spark, etc.).
• Familiarity with cloud platforms (AWS, GCP, or Azure) for model deployment and data processing.
• Experience with statistical modeling, predictive analytics, and time-series analysis.
• Knowledge of natural language processing (NLP) or computer vision applications in insurance is a plus.
• Soft Skills:
• Excellent communication skills to explain complex AI/ML models to non-technical stakeholders.
• Strong problem-solving abilities with attention to detail.
• Ability to work in a fast-paced, collaborative environment.
• Preferred Qualifications
• Experience with insurance-specific data sources such as claims data, policyholder data, or telematics.
• Knowledge of regulatory and compliance standards in the insurance industry.
• Understanding of actuarial science or certification (e.g., ACAS, FCAS) is a bonus.