Actuarial Analyst

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Requirements:

• Minimum of 4 years of experience working in actuarial analysis, data science, or pricing and underwriting, within the insurance industry, preferably within a startup environment
• Bachelor’s degree in Actuarial Science, Mathematics, Statistics, Data Science, Finance, Accounting, or a related field.
• Proficiency in statistical modeling techniques (e.g., regression analysis, hypothesis testing) and understanding of financial exposure and risk metrics.
• Experience with tools such as Python, R, SQL, or other statistical software as well as data modeling/analysis tools like Looker, PowerBI.
• Advanced knowledge of Excel.
• Strong analytical mindset, with a passion for diving into numbers and making data-driven decisions.
• Familiarity with actuarial processes (pricing, reserving, risk assessment).
• Strong organizational and project management skills.
• Demonstrated ability to lead initiatives, build out processes or functions from scratch, especially in a startup or fast-paced environment while working cross functionally.
• Excellent organizational and time management skills.
• Ability to adapt to a fast-paced, dynamic startup environment and contribute to a positive and collaborative culture.
• Proactive and solution-forward, bias for action.

Responsibilities:

• Analyze and interpret insurance risks, with a strong focus on the statistical relationships that affect risk outcomes.
• Provide insights into device protection risks, pricing strategies, and trends in insurtech.
• Develop and maintain statistical models to analyze financial exposure, risk, and performance of insurance products.
• Use advanced data science techniques, such as predictive modeling, machine learning, and hypothesis testing to uncover trends and inform decision-making.
• Collaborate cross-functionally with teams such as Product, Engineering, and Finance to build out actuarial functions and initiatives.
• Work alongside data analysts to ensure our actuarial models are aligned with the company’s long term goals for data and machine learning.
• Create solutions to improve our systems and processes.
• Ensure that all actuarial work complies with insurance regulations and industry standards, adapting to changes in the insurtech landscape.
• Coordinate with underwriting partners around data organization and alignment.
• Prepare and present reports and analysis to senior management, underwriters, and other stakeholders.