Actuarial Data Science Analyst (Insurance Hybrid role)

PA Compensation Rating Bureau.; Philadelphia (Philadelphia County); Hybrid; USD 90,000 - 140,000; Full time

Job summary

PA Compensation Rating Bureau in Philadelphia is seeking a data analytics professional to support actuarial research, business intelligence, and data analytics initiatives through statistical analysis, data engineering, and model development.

You will work with large datasets using Python, R, SQL, and Snowflake to automate processes, build dashboards, and translate research into actionable business insights for technical and non-technical audiences.

Qualifications

• Bachelor’s degree in Mathematics/Statistics/Economics or CS strongly preferred.
• 3–6 years experience in related field.
• Strong programming skills in Python and R; proficient in data manipulation and statistical analysis.

Responsibilities

• Conduct statistical analyses and actuarial/research models.
• Design and maintain data pipelines and automated processes using Python, R, SQL, Snowflake, or other languages.
• Extract, validate, and analyze data from multiple sources to support research and business initiatives.
• Develop reports and visualizations; present findings to technical and non-technical audiences.

Skills

Python

R

SQL

Snowflake

Data manipulation

Statistical analysis

Process automation

Communication

Multitasking

Education

Bachelor's degree in Mathematics/Statistics/Economics/CS

Actuarial Science or Data Science-related Masters

Tools

SQL

Snowflake

Excel

Power BI

Tableau

Pyramid

Job description

Job Summary:

This position supports actuarial research, business intelligence, and data analytics initiatives through statistical analysis, data engineering, and analytical model development. The employee is responsible for designing and maintaining data pipelines, performing actuarial and statistical analyses, developing analytical tools and dashboards, and communicating research findings and recommendations to technical and non-technical audiences.

The position works with large datasets using programming languages such as Python and R, SQL, and Snowflake to automate processes, conduct research, and support strategic business decisions. Responsibilities include developing reports and visualizations, evaluating emerging analytical methods, and participating in multiple concurrent projects, including research studies, data integration, predictive analytics, and business intelligence initiatives.

Essential Responsibilities:

• Responsible for statistical analyses, actuarial and/or research models
• Design and maintain data pipelines, analytical models, and automated processes using Python, R, SQL, Snowflake, or other programming languages.
• Extract, validate, and analyze data from multiple sources to support research and business initiatives.
• Drawing inferences, developing reports, and presenting analysis and recommendations to technical and non-technical audiences.
• Participates in multiple research, business intelligence, and data analytics projects simultaneously

Requirements:

Education: Bachelor’s Degree – B.A. / B.S. Mathematics, Statistics, Economics or Computer Science strongly preferred. A degree in Actuarial Science or a Masters in Data Science related field a plus.

Experience: 3 to 6 years experience in related field.

Skills Required: Strong organizational, communication, written, and analytical skills with the ability to work independently and manage multiple priorities. Programming proficiency in Python and R is a core requirement, including experience with data manipulation, statistical analysis, and process automation. Experience with SQL, Snowflake, and advanced Excel is required. Experience with business intelligence platforms such as Pyramid, Power BI, or Tableau is preferred. The candidate must communicate effectively with all levels of personnel and external contacts.

Preferred Qualifications

• Actuarial background or experience in the property & casualty insurance industry is a plus.

Work Hours:

Normal PCRB hybrid Flex time is available. Employee must be flexible when needed as projects or deadlines may sometimes necessitate extended hours.