Sr. Actuarial Data Analyst

Who We Are

ECLARO is an award-winning professional services firm headquartered in New York City and operating in the U.S., Philippines and Canada, additionally supporting clients in the UK, Ireland and Australia. We are dedicated to a singular purpose: providing the Right People with the right expertise, business knowledge, skill sets, dedication and passion to solve business challenges for global clients ranging from innovative start-ups to Fortune 50 companies. "Work Hard. Give Back. Have Fun." is one of our favorite sayings, and we live it every day. Supporting employees and colleagues, serving clients and giving back to our communities

About the Role:

We are seeking a hands-on Sr. Actuarial Data Analyst to develop, maintain, and optimize actuarial models, processes, and analytical tools. This role will work closely with actuaries and other stakeholders to support month-end processes, rate change calculations, and ad-hoc analyses, serving as a liaison between the Information technology team and the actuarial team. The ideal candidate has a strong technical background in Python, R, and SQL, with experience in NoSQL databases, Power BI, and Excel. This role requires a mix of actuarial analysis and data modeling skills, ensuring accuracy and efficiency in delivering data-driven insights.

• Job Title: Sr. Actuarial Data Analyst
• Work Schedule: Night shift
• Location: Remote

Key Responsibilities:

Model Development & Maintenance

• Develop and maintain actuarial models and data-driven processes using Python, R, and SQL to support insurance pricing, reserving, and risk management.

• Implement and enhance month-end processes, rate change calculations, and ad-hoc analyses with a focus on completeness, accuracy, and consistency to ensure data is of the highest quality.

• Work with the Actuarial and Financial Planning and Analysis (FP&A) teams to automate and improve model performance using Python-based scripting and automation.

• Ensure accuracy, consistency, and efficiency of actuarial models and methodologies.

Traditional Actuarial Tasks

• Support reserving analysis to estimate unpaid claim liabilities primarily in partnership with internal and external actuaries.

• Develop and maintain loss development triangles and incurred but not reported (IBNR) calculations both based on financial and operational data (e.g., claims closing ratios).

• Support the development and validation of actuarial assumptions for pricing, reserving, and forecasting.

• Develop and regularly report on rate change calculations including bifurcation of exposure changes from pure rate by line of business.

Financial Modeling & Risk Assessment

• Conduct stress testing and scenario analysis to assess financial impacts.

• Develop, update, and maintain models for predictive analytics, profitability analysis, and business planning.

• Assist in forecasting financial performance and evaluating risk exposure.

Data Management & Analysis

• Write complex queries in SQL to extract and transform data, leveraging Python for advanced data processing and automation.

• Build queries with a controls-oriented focus to ensure accuracy, completeness, Analyze large datasets using Python libraries such as Pandas and NumPy to identify trends, patterns, and opportunities for optimization.

• Develop and implement Python scripts to automate data processing, actuarial calculations, and reporting workflows.

Collaboration & Support

• Work closely with the Actuarial and FP&A teams to support financial planning, forecasting, and profitability analysis by providing robust data models and insights.

• Partner with Data Engineers to optimize data workflows and ensure seamless data ingestion.

• Communicate technical results and methodologies to non-technical stakeholders in a clear and concise manner.

Reporting & Visualization

• Develop reports, dashboards, and data visualizations using Power BI and Excel.

• Ensure that reports comply with regulatory requirements and industry standards.

• Present findings and insights to key stakeholders to drive business decisions.

Qualifications

• Bachelor's degree in Mathematics, Statistics, Actuarial Science, Data Science, or a related field.

• 3+ years of experience in actuarial analysis, data modeling, or a related technical role.

• Understanding of Commercial P&C Insurance operations and data, Commercial Auto experience a-plus.

• Strong programming skills in Python, and SQL. Knowledge of R a-plus.

• Experience with NoSQL databases (e.g., MongoDB, DynamoDB) is a plus.

• Proficiency in Power BI and Excel for data visualization and reporting.

• Strong understanding of actuarial concepts, insurance data, and financial modeling.

Preferred Skills

• Experience in automating data workflows and ensuring efficient data ingestion for actuarial processes.

• Knowledge of AI, machine learning techniques and exposure to predictive modeling.

Soft Skills

• Excellent communication and interpersonal skills.

• Strong attention to detail, controls orientation, and commitment to delivering high-quality work.

• Ability to handle multiple projects concurrently and meet deadlines.

• Enthusiasm for learning new technologies and staying current in the industry.