AKKO · 8 hours ago

Actuarial Analyst

New York, NY (Remote)

Full-time

Remote

Mid Level

$80K/yr - $110K/yr

4+ years exp

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ElectronicsInsurance

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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.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Actuarial AnalysisStatistical ModelingData SciencePythonSQLRLookerPowerBIExcelRegression AnalysisHypothesis TestingFinancial ExposureRisk MetricsData-Driven Decision MakingProject Management

Required

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.