Salary for Entry-level / Junior Actuarial Analyst during 2024

Salary details

The average entry-level / junior 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. 22, 2024

Top 20 Job Tags for Entry-level / Junior Actuarial Analyst roles

The three most common job tag items assiciated with entry-level / junior 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 | 40 jobs R | 36 jobs Mathematics | 35 jobs Statistics | 34 jobs SQL | 31 jobs Excel | 26 jobs SAS | 19 jobs Research | 13 jobs Economics | 12 jobs Data Analytics | 12 jobs Finance | 12 jobs Tableau | 9 jobs Consulting | 9 jobs Data analysis | 9 jobs Power BI | 8 jobs Data management | 7 jobs Privacy | 7 jobs Machine Learning | 6 jobs Engineering | 5 jobs Data visualization | 5 jobs

Top 20 Job Perks/Benefits for Entry-level / Junior Actuarial Analyst roles

The three most common job benefits and perks assiciated with entry-level / junior Actuarial Analyst job listings are Career development, Insurance and Health care. 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 | 32 jobs Insurance | 23 jobs Health care | 16 jobs Flex hours | 15 jobs Competitive pay | 10 jobs Flex vacation | 8 jobs Parental leave | 6 jobs Team events | 6 jobs Medical leave | 6 jobs Salary bonus | 6 jobs Equity / stock options | 4 jobs Fertility benefits | 4 jobs 401(k) matching | 2 jobs Wellness | 2 jobs Startup environment | 2 jobs Relocation support | 2 jobs

Salary Composition

The salary composition for an entry-level or junior actuarial analyst in AI/ML/Data Science can vary significantly based on factors such as region, industry, and company size. Typically, the salary is composed of a fixed base amount, which forms the bulk of the compensation package. In regions with a high cost of living or in industries like finance and tech, the base salary tends to be higher. Bonuses are often performance-based and can range from 5% to 20% of the base salary, depending on the company's profitability and individual performance metrics. Additional remuneration might include stock options, especially in tech companies, and benefits such as health insurance, retirement contributions, and professional development allowances. Larger companies may offer more comprehensive benefits packages compared to smaller firms.

Increasing Salary

To increase your salary from an entry-level position, consider pursuing further education or certifications that are relevant to your field. Gaining experience in high-demand areas such as machine learning, data engineering, or advanced statistical analysis can make you more valuable to employers. Networking within the industry and seeking mentorship can also provide opportunities for advancement. Additionally, demonstrating leadership skills and taking on more responsibility in your current role can position you for promotions and salary increases. Exploring opportunities in different regions or industries where salaries are higher can also be a strategic move.

Educational Requirements

Most entry-level actuarial analyst positions in AI/ML/Data Science require at least a bachelor's degree in a related field such as mathematics, statistics, computer science, or actuarial science. Some employers may prefer candidates with a master's degree, especially for roles that involve complex data analysis or machine learning. Coursework in data analysis, programming, and statistical modeling is often essential. A strong foundation in mathematics and analytical skills is crucial for success in this role.

Helpful Certifications

Certifications can enhance your qualifications and demonstrate your commitment to professional development. Common certifications that are beneficial for this role include:

• Associate of the Society of Actuaries (ASA): This certification is highly regarded in the actuarial field and covers essential topics such as probability, financial mathematics, and actuarial models.
• Certified Analytics Professional (CAP): This certification is valuable for demonstrating expertise in data analytics and decision-making.
• Data Science Certifications: Programs like those offered by Coursera, edX, or DataCamp can provide practical skills in data science and machine learning.

Experience Requirements

For an entry-level position, employers typically look for candidates with some relevant internship or project experience. This could include experience with data analysis, statistical modeling, or programming in languages such as Python or R. While direct work experience in AI/ML may not be required, familiarity with these concepts and tools is advantageous. Demonstrating experience through academic projects, internships, or personal projects can be beneficial.

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