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 Pricing and Systems Actuary, 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 Python and in Excel. Building a system ultimately allows the team to help steer the portfolio more 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, including P&C insurance Strongly preferred but not required: ACAS, FCAS (this a hybrid actuarial and analytics role) 2+ years experience with Python Bachelor/Master in a quantitative discipline (computer science, actuarial science, mathematics, statistics, economics, physics, engineering, or related field) A passion for solving challenging mathematical problems and an interest in exploring new machine learning tools and technologies An entrepreneurial mindset with a bias for action over perfection, and are, 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.) Communications skills for translating technical or statistical analysis results into business recommendations Our estimated pay range for this role is $165,000 to $190,000. Base salary is determined by a variety of factors, including but not limited to, market data, location, internal equitability, and experience. We are committed to being a welcoming and inclusive workplace for everyone, and we are intentional about making sure people feel respected, supported and connected at work—regardless of who you are or where you come from. We value and celebrate our differences and we believe being open about who we are allows us to do the best work of our lives. We are an Equal Opportunity Employer. We do not discriminate against qualified applicants or employees on the basis of race, color, religion, gender identity, sex, sexual preference, sexual identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, military status, or any other characteristic protected by federal, state, or local law, rule, or regulation. #J-18808-Ljbffr Counterpart