Role and Responsibilities Overview:

We are seeking a highly skilled Part Qualified or Nearly Qualified Actuary to independently support the development of advanced pricing models and analytical frameworks that drive profitable growth across the clients Property & Casualty portfolio. This role will combine deep actuarial expertise with modern data science techniques (using ML/AI) to design, implement, and maintain predictive pricing models.

Predictive Modeling:

- Design and implement advanced predictive models for pricing using techniques such as Generalized Linear Models (GLMs), machine learning models (Decision Trees, Random Forest), and credibility methods.

- Identify risk segmentation opportunities and develop rating variables that improve pricing precision.

- Conduct model validation, monitoring, and recalibration to ensure robust performance.

- Build scalable analytics pipelines using tools such as Emblem, Radar, Python, R, SQL, and other cloud-based data platforms.

- Support initiatives to modernize pricing analytics through automation, advanced modeling techniques including ML/AI, and improved data infrastructure.

- Monitor emerging analytics on major trends, univariate and multi-variate analysis and incorporate new methods to maintain competitive pricing capabilities.

- Develop automated workflows for data ingestion, preparation, and model deployment.

- Apply statistical and machine learning methods to enhance predictive accuracy and business insights.

- Partner with data engineering teams to implement scalable solutions in cloud-based analytics platforms.

- Evaluate model performance and ensure regulatory and actuarial standards are met.

- Communicate model results and recommendations to senior leadership.

Pricing Data Mart Development:

- Design, build, and maintain robust Data Marts for actuarial datasets (policy, claims, exposure, reinsurance).

- Develop and optimize ETL pipelines to integrate data from multiple source systems.

- Perform independent research, analyze, and present data as assigned.

- Design and development of a centralized Pricing Data Mart (PDM) to support scalable pricing analytics.

- Define data structures, actuarial datasets, and feature libraries used for modeling and pricing analyses.

- Ensure data governance, documentation, and reproducibility of pricing datasets.

Candidate Profile:

- Bachelors/Master's degree in engineering, economics, mathematics, actuarial sciences, statistics.

- Affiliation to IAI, IFOA, CAS or SOA with 4+ actuarial exams.

- 3-7 years of experience in P&C ratemaking, pricing, or regulatory filings.

- Deep understanding of insurance regulatory environments and filing requirements.

- Familiarity with cloud data ecosystems (e.g., Snowflake, Databricks, or AWS analytics tools).

- Knowledge of general insurance domain and P&C actuarial concepts is a must.

- Advanced skills in Excel, VBA, SAS, SQL, R, Python and other relevant tools for data analysis and modeling.

- Excellent analytical and problem-solving skills, with the ability to analyze large datasets and make data-driven decisions.

- Strong communication skills, including the ability to effectively communicate complex actuarial concepts to both technical and non-technical stakeholders.

- Ability to work independently and collaboratively in a team-oriented environment.

- Detail-oriented with strong organizational and time management skills.

- Ability to adapt to changing priorities and deadlines in a fast-paced environment.