Data Scientist

About the role

Insurity is looking for a Data Scientist to design and deploy predictive models that help insurance clients make data‑driven decisions. You will work with structured and unstructured data, leverage AWS services, and collaborate closely with product and engineering teams to bring models into production.

Responsibilities

• Build predictive models using GLM, GBM, Random Forest, and XGBoost.
• Perform feature engineering, selection, and transformation to improve model accuracy.
• Analyze diverse datasets to extract insights that guide model development.
• Integrate third‑party data sources to enrich model inputs.
• Work with product and engineering squads to embed models into live systems.
• Utilize AWS SageMaker and EC2 for model training, deployment, and scaling.
• Document modeling choices and present findings to both technical and non‑technical audiences.
• Monitor model performance over time and implement necessary updates.

Eligibility

• 1‑3 years of experience in data science or predictive modeling.
• Strong grasp of GLM and machine‑learning algorithms such as GBM, XGBoost, and Random Forest.
• Proficiency in Python and libraries like scikit‑learn, pandas, and NumPy.
• Hands‑on experience with AWS tools, especially SageMaker and EC2.
• Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field.
• Excellent communication skills and ability to work in cross‑functional teams.

Skills

• Python programming
• AWS services (SageMaker, EC2)
• Git version control
• Statistical modeling (GLM)
• Machine‑learning algorithms (GBM, Random Forest, XGBoost)
• Data manipulation with pandas and NumPy
• Model evaluation and feature engineering

Benefits

• Opportunity to work on cutting‑edge insurance analytics.
• Access to cloud‑native tools and a collaborative environment.
• Professional growth through cross‑team projects.