Salary for Entry-level / Junior Actuarial Analyst in United States during 2024

Salary details

The average entry-level / junior Actuarial Analyst salary lies between USD 56,000 and USD 120,000 in the United States. 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.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Nov. 17, 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 Statistics. 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 | 30 jobs R | 27 jobs Statistics | 26 jobs Mathematics | 26 jobs SQL | 25 jobs Excel | 20 jobs SAS | 17 jobs Research | 10 jobs Data Analytics | 10 jobs Economics | 9 jobs Finance | 9 jobs Consulting | 8 jobs Data analysis | 8 jobs Tableau | 6 jobs Power BI | 5 jobs Data management | 5 jobs Privacy | 5 jobs Machine Learning | 4 jobs Data visualization | 4 jobs Predictive modeling | 4 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 | 25 jobs Insurance | 17 jobs Health care | 11 jobs Flex hours | 9 jobs Competitive pay | 9 jobs Flex vacation | 7 jobs Parental leave | 6 jobs Team events | 6 jobs Medical leave | 6 jobs Salary bonus | 5 jobs Fertility benefits | 4 jobs Equity / stock options | 3 jobs 401(k) matching | 2 jobs Startup environment | 2 jobs Relocation support | 2 jobs Wellness | 1 jobs

Salary Composition

The salary for an entry-level or junior actuarial analyst in the AI/ML/Data Science field typically consists of a base salary, performance bonuses, and sometimes additional remuneration such as stock options or profit-sharing. The base salary is the fixed component and usually makes up the majority of the total compensation package. Performance bonuses can vary significantly depending on the company’s performance and individual achievements. Additional remuneration might include benefits like health insurance, retirement contributions, and sometimes equity in the company, especially in tech startups. The composition can vary by region, with tech hubs like San Francisco or New York offering higher base salaries but potentially less in bonuses compared to other regions. Industry also plays a role; for instance, financial services might offer higher bonuses compared to academia or public sector roles. Larger companies might offer more comprehensive benefits packages, while smaller companies might compensate with higher base salaries or equity options.

Steps to Increase Salary

To increase your salary from an entry-level position, consider the following strategies:

• Skill Enhancement: Continuously upgrade your skills in AI/ML and data science. Specializing in high-demand areas like deep learning, natural language processing, or big data analytics can make you more valuable.
• Certifications: Obtain relevant certifications that can validate your skills and knowledge, making you more competitive.
• Networking: Build a strong professional network. Attend industry conferences, join professional groups, and connect with peers and mentors who can provide guidance and opportunities.
• Performance Excellence: Consistently exceed performance expectations in your current role. Demonstrating your ability to deliver results can position you for promotions and salary increases.
• Advanced Education: Consider pursuing further education, such as a master’s degree or specialized courses, to deepen your expertise and open up higher-level opportunities.

Educational Requirements

Most entry-level actuarial analyst positions in AI/ML/Data Science require at least a bachelor’s degree in a related field. Common fields of study include mathematics, statistics, computer science, actuarial science, or engineering. A strong foundation in quantitative skills is essential, and coursework in data analysis, programming, and machine learning is highly beneficial. Some positions may prefer candidates with a master’s degree, especially for roles that require more specialized knowledge or research capabilities.

Helpful Certifications

Several certifications can enhance your qualifications for an actuarial analyst role in AI/ML/Data Science:

• Associate of the Society of Actuaries (ASA): This is a common certification for actuaries and demonstrates a solid understanding of actuarial principles.
• Certified Analytics Professional (CAP): This certification is valuable for demonstrating expertise in analytics and data science.
• Data Science Certifications: Certifications from platforms like Coursera, edX, or DataCamp in data science or machine learning can be beneficial.
• Programming Certifications: Certifications in programming languages such as Python or R can also be advantageous.

Experience Requirements

For an entry-level position, employers typically look for candidates with some practical experience, which can be gained through internships, co-op programs, or relevant project work during your studies. Experience with data analysis, statistical modeling, and programming is often required. Familiarity with machine learning frameworks and tools, as well as experience in handling large datasets, can be a plus. While extensive professional experience is not expected, demonstrating hands-on experience through projects or internships can set you apart.

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