Pricing and Systems Actuary

Counterpart is an insurtech platform reimagining management and professional liability for the modern workplace. We believe that when businesses lead with clarity and confidence, they become more resilient, more innovative, and better prepared for what’s ahead. That’s why we built the first Agentic Insurance™ system — where advanced AI and deep insurance expertise come together to proactively assess, mitigate, and manage risk.

Backed by A‑rated carriers and trusted by brokers nationwide, our platform helps small businesses grow with confidence. Join us in shaping a smarter future, helping businesses Do More With Less Risk®.

As a Data Science Actuary, you will

You will balance being a prolific individual contributor to initiatives at the intersection of data science and traditional actuarial work. You will help bridge the gap between the Data & Insurance teams by leveraging actuarial techniques such as pricing and risk modeling as well as new techniques such as machine learning and programming. In addition, you will contribute to the culture, rituals, and processes that underpin a high‑functioning team and the organization more broadly.

Responsibilities

• Build and maintain new efficient/expansive rating systems and related models in Excel and in Python. There is a core programming component to this role that allows us to build and steer effectively.

• Build and maintain risk/simulation models to help analyze and steer the business.

• Research ways to leverage industry data to enhance current rating, new/current admitted filings, and provide guidance to underwriting.

• Develop complex analyses of our underwriting, operations, business development, product performance, and user experience.

• Assist the data science, operations, and insurance teams with ad hoc analysis, data normalization, data cleansing and process improvement.

• Support the integration and production of new data sources in a manner that minimizes development cycles while maximizing potential business applications.

• Continuously challenge how we can improve our underwriting and operations.

• Maintain a clean production environment such that the data models can be easily interpreted and built upon by other data science and engineering team members.

• Present your work, findings, and opinions to both technical and non‑technical stakeholders.

Qualifications

• Minimum of 3 years of total work experience.

• Bachelor/Master in a quantitative discipline (computer science, actuarial science, mathematics, statistics, economics, physics, engineering, or related field).

• Preferred but not required: ACAS, FCAS (this a hybrid actuarial and analytics role).

• Experience and interest in data science techniques (e.g. Machine Learning).

• An entrepreneurial mindset, interested in building the future.

• Preferred: domain knowledge in management/professional liability.

• Ability to balance competing priorities and focus on key initiatives, by estimating timelines and keeping team/documentation updated with the status of projects.

• Experience and excitement using modern cloud computing and cloud databases (i.e. AWS, Snowflake, etc.).

• A passion for solving challenging mathematical problems and an interest in exploring new machine learning tools and technologies.

• 2+ years experience with Python.

• Communications skills for translating technical or statistical analysis results into business recommendations.

• Bias to practical action and creativity using data (we value past or present projects that support this).

Who you will work with

• Tanner Hackett, CEO & Founder:
Having founded two other major startups, including Button and Lazada, Tanner now spends his time focused on mental health through his philanthropy, Open minded.org , in addition to reading, surfing, yoga, and enjoying the outdoors.

• Stanley Wang, Senior Director, Pricing Analytics:
Before joining Counterpart, Stanley worked as an actuary within the pricing solutions and methods team at USAA to combine actuarial pricing with data science models. Before that, he was a leading data scientist for Digital Partners, a Munich Re Company where he specialized in building data science models and insights for…