Data Scientist

Overview

We are seeking a skilled Data Scientist to join our Insurance Underwriting team. The ideal candidate will specialize in developing and deploying machine learning models and performing advanced data manipulation to enhance underwriting processes, improve risk assessment, and drive data-informed decision-making. This role requires a strong background in machine learning, statistical modeling, and data analysis, with a focus on insurance industry applications.

Key Responsibilities

Model Development : Design, build, and deploy machine learning models to predict risk, pricing, and customer behavior for insurance underwriting purposes.

Data Manipulation and Analysis : Clean, preprocess, and analyze large datasets from diverse sources (, claims data, customer demographics, policy data) to uncover actionable insights.

Feature Engineering : Identify and create relevant features from structured and unstructured data to improve model performance and underwriting accuracy.

Risk Assessment : Develop models to enhance risk segmentation, loss prediction, and premium pricing, ensuring alignment with actuarial standards.

Model Validation : Evaluate model performance using appropriate metrics (, AUC, RMSE) and ensure models meet regulatory and business requirements.

Collaboration : Work closely with underwriters, actuaries, and IT teams to integrate models into underwriting workflows and systems.

Data Visualization : Create clear, actionable visualizations and reports to communicate insights and model outcomes to non-technical stakeholders.

Continuous Improvement : Monitor and refine models to adapt to changing market conditions, regulatory requirements, and emerging risks.

Compliance : Ensure all models and data processes comply with insurance regulations (, GDPR, NAIC guidelines) and internal policies.

Qualifications

Education : Master's or in Data Science, Statistics, Computer Science, Mathematics, or a related field. Bachelor's degree with equivalent experience may be considered.

Experience :

• years of experience in data science, with a focus on machine learning and data manipulation.

Prior experience in the insurance industry, particularly in underwriting or risk modeling, is highly preferred.

Technical Skills :

Proficiency in Python or R for data analysis and model development (, scikit-learn, TensorFlow, PyTorch, XGBoost).

Strong experience with SQL for querying and manipulating large datasets.

Familiarity with data visualization tools (, Tableau, Power BI, Matplotlib, Seaborn).

Knowledge of cloud platforms (, AWS, Azure, GCP) for model deployment and data processing is a plus.

Domain Knowledge :

Understanding of insurance underwriting processes, risk assessment, and actuarial principles.

Familiarity with insurance-specific datasets (, claims, telematics, policy data).

Soft Skills :

Excellent problem-solving and analytical skills.

Strong communication skills to translate complex technical concepts to non-technical stakeholders.

Ability to work collaboratively in a fast-paced, cross-functional environment.

Preferred Qualifications

Experience with advanced machine learning techniques, such as deep learning, natural language processing (NLP), or ensemble methods, applied to insurance use cases.

Knowledge of regulatory frameworks in the insurance industry (, Solvency II, HIPAA).

Familiarity with big data tools (, Spark, Hadoop) for processing large-scale datasets.

Experience deploying models in production environments and monitoring their performance.

Our benefits package includes : (EXCLUDE on perm placements)