Actuarial Analyst Salary in 2024

Salary details

The average Actuarial Analyst salary lies between USD 56,000 and USD 120,000 globally. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Dec. 15, 2024

Top 20 Job Tags for Actuarial Analyst roles

The three most common job tag items assiciated with Actuarial Analyst job listings are Python, R and Mathematics. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

Python | 62 jobs R | 56 jobs Mathematics | 56 jobs Statistics | 52 jobs SQL | 43 jobs Excel | 39 jobs SAS | 25 jobs Research | 21 jobs Economics | 21 jobs Finance | 19 jobs Tableau | 17 jobs Data Analytics | 16 jobs Power BI | 15 jobs Machine Learning | 11 jobs Consulting | 11 jobs Data management | 11 jobs Data analysis | 9 jobs Testing | 8 jobs Physics | 8 jobs Engineering | 7 jobs

Top 20 Job Perks/Benefits for Actuarial Analyst roles

The three most common job benefits and perks assiciated with Actuarial Analyst job listings are Career development, Insurance and Flex hours. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:

Career development | 51 jobs Insurance | 34 jobs Flex hours | 29 jobs Health care | 26 jobs Flex vacation | 14 jobs Competitive pay | 14 jobs Salary bonus | 11 jobs Team events | 10 jobs Parental leave | 9 jobs Medical leave | 8 jobs Equity / stock options | 6 jobs Startup environment | 6 jobs Fertility benefits | 4 jobs 401(k) matching | 3 jobs Wellness | 3 jobs Relocation support | 2 jobs

Salary Composition

The salary composition for an AI/ML/Data Science role can vary significantly based on factors such as region, industry, and company size. Generally, the salary is composed of a fixed base salary, a performance-based bonus, and additional remuneration such as stock options or other benefits. In tech hubs like Silicon Valley, the base salary might be higher, but the cost of living is also elevated. In contrast, regions with a lower cost of living might offer a smaller base salary but could compensate with a more substantial bonus or stock options. Industry-wise, tech companies and financial institutions often offer competitive packages, while smaller startups might offer lower base salaries but compensate with equity. Larger companies tend to provide more structured bonus schemes and additional benefits like health insurance, retirement plans, and professional development opportunities.

Increasing Salary

To increase your salary from the position of an Actuarial Analyst transitioning into AI/ML/Data Science, consider the following steps:

• Skill Enhancement: Continuously upgrade your skills in AI/ML through online courses, workshops, and certifications. Specializing in a niche area can make you more valuable.
• Networking: Engage with professionals in the field through conferences, seminars, and online platforms like LinkedIn. Networking can open doors to higher-paying opportunities.
• Advanced Education: Pursuing a master's degree or Ph.D. in a related field can significantly boost your earning potential.
• Performance and Results: Demonstrating a track record of successful projects and tangible results can position you for promotions and salary increases.
• Negotiation: When offered a new position or during performance reviews, negotiate your salary based on market research and your contributions.

Educational Requirements

Most AI/ML/Data Science roles require at least a bachelor's degree in a related field such as computer science, mathematics, statistics, or engineering. However, many employers prefer candidates with a master's degree or Ph.D. due to the complex nature of the work. A strong foundation in mathematics and statistics is crucial, as is proficiency in programming languages like Python or R.

Helpful Certifications

Certifications can enhance your credibility and demonstrate your commitment to the field. Some valuable certifications include:

• Certified Data Scientist (CDS)
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate
• AWS Certified Machine Learning – Specialty
• TensorFlow Developer Certificate

These certifications can help you stand out in a competitive job market and may lead to higher salary offers.

Experience Requirements

Typically, employers look for candidates with at least 2-5 years of experience in data analysis, machine learning, or a related field. Experience in handling large datasets, developing machine learning models, and deploying AI solutions is highly valued. Internships, research projects, or previous roles in data-centric positions can also count towards this experience.

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