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

Salary details

The average entry-level / junior Research Analyst salary lies between USD 70,400 and USD 145,000 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: Dec. 22, 2024

Salary trend

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

The three most common job tag items assiciated with entry-level / junior Research Analyst job listings are Research, Python 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:

Research | 283 jobs Python | 183 jobs Statistics | 178 jobs Excel | 147 jobs R | 138 jobs Data analysis | 113 jobs SQL | 100 jobs Economics | 99 jobs Mathematics | 89 jobs Engineering | 83 jobs Finance | 77 jobs Machine Learning | 70 jobs Security | 62 jobs SAS | 62 jobs Computer Science | 57 jobs Power BI | 53 jobs Tableau | 51 jobs Market research | 51 jobs Data visualization | 37 jobs Stata | 37 jobs

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

The three most common job benefits and perks assiciated with entry-level / junior Research Analyst job listings are Career development, Health care and Equity / stock options. 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 | 174 jobs Health care | 129 jobs Equity / stock options | 73 jobs Flex hours | 70 jobs Competitive pay | 62 jobs Startup environment | 58 jobs Insurance | 52 jobs Team events | 44 jobs Flex vacation | 41 jobs Wellness | 35 jobs Salary bonus | 34 jobs Medical leave | 33 jobs 401(k) matching | 22 jobs Parental leave | 19 jobs Conferences | 14 jobs Transparency | 7 jobs Relocation support | 6 jobs Flexible spending account | 6 jobs Fitness / gym | 5 jobs Fertility benefits | 4 jobs

Salary Composition

In the United States, the salary composition for an entry-level or junior research analyst in AI/ML/Data Science typically includes a base salary, performance bonuses, and sometimes additional remuneration such as stock options or benefits. The base salary is the fixed component and usually constitutes 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 stock options, especially in tech companies or startups, and benefits like health insurance, retirement plans, and paid time off. The composition can vary by region, with tech hubs like San Francisco or New York offering higher base salaries but potentially less in bonuses due to the high cost of living. Industry also plays a role; for instance, finance and tech industries might offer more lucrative packages compared to academia or non-profits. Company size can influence the package as well, with larger companies often providing more comprehensive benefits and smaller companies potentially offering more equity.

Career Advancement

To increase your salary from an entry-level position, consider gaining specialized skills or certifications that are in high demand, such as expertise in deep learning, natural language processing, or big data technologies. Pursuing a master's degree or Ph.D. in a related field can also open doors to higher-level positions. Networking within the industry and seeking mentorship can provide insights into career advancement opportunities. Additionally, gaining experience in managing projects or leading teams can position you for roles with greater responsibility and higher pay. Transitioning to a more lucrative industry or moving to a region with higher salary standards can also be effective strategies.

Educational Requirements

Most entry-level positions in AI/ML/Data Science require at least a bachelor's degree in a related field such as computer science, data science, mathematics, statistics, or engineering. However, a master's degree is increasingly preferred, as it provides a deeper understanding of complex algorithms and data analysis techniques. Some roles may also consider candidates with degrees in other quantitative fields, provided they have relevant skills and experience.

Helpful Certifications

Certifications can be a valuable addition to your resume, demonstrating your commitment to the field and your expertise in specific areas. Some popular certifications include:

• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate
• IBM Data Science Professional Certificate
• TensorFlow Developer Certificate

These certifications can help you stand out in the job market and may be particularly beneficial if you lack formal education in AI/ML.

Experience Requirements

For entry-level positions, employers typically look for candidates with some practical experience, which can be gained through internships, co-op programs, or relevant projects during your studies. Experience with programming languages such as Python or R, familiarity with machine learning frameworks like TensorFlow or PyTorch, and a solid understanding of data analysis and visualization tools are often required. While extensive professional experience is not expected, demonstrating your ability to apply theoretical knowledge to real-world problems is crucial.

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