Research Analyst Salary in United States during 2023

Salary details

The average Research Analyst salary lies between USD 64,000 and USD 135,960 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. 24, 2024

Salary trend

Top 20 Job Tags for Research Analyst roles

The three most common job tag items assiciated with Research Analyst job listings are Research, Python and Excel. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

Research | 186 jobs Python | 130 jobs Excel | 95 jobs SQL | 82 jobs Economics | 70 jobs Statistics | 67 jobs Engineering | 62 jobs Data analysis | 62 jobs R | 61 jobs Consulting | 53 jobs Privacy | 51 jobs Market research | 45 jobs Finance | 41 jobs Machine Learning | 35 jobs Power BI | 29 jobs Security | 27 jobs Tableau | 23 jobs Data visualization | 23 jobs Mathematics | 23 jobs Testing | 19 jobs

Top 20 Job Perks/Benefits for Research Analyst roles

The three most common job benefits and perks assiciated with Research Analyst job listings are Career development, Flex hours and Team events. Below you find a list of the 20 most occuring job perks or benefits in 2023 and the number of open jobs that where offering them during that period:

Career development | 95 jobs Flex hours | 72 jobs Team events | 54 jobs Health care | 51 jobs Startup environment | 47 jobs Equity / stock options | 38 jobs Competitive pay | 38 jobs Insurance | 33 jobs Salary bonus | 32 jobs 401(k) matching | 30 jobs Medical leave | 27 jobs Flex vacation | 26 jobs Wellness | 24 jobs Parental leave | 17 jobs Conferences | 15 jobs Fitness / gym | 8 jobs Home office stipend | 6 jobs Paid sabbatical | 5 jobs Fertility benefits | 4 jobs Lunch / meals | 3 jobs

Salary Composition

The salary for a Research Analyst in AI/ML/Data Science typically consists of a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually makes up the majority of the total compensation package. Bonuses can vary significantly depending on the company's performance, individual performance, and industry standards. In tech-heavy regions like Silicon Valley, bonuses and stock options might form a larger portion of the total compensation compared to other regions. Larger companies or those in high-demand industries may offer more competitive bonus structures and additional perks, such as health benefits, retirement plans, and professional development opportunities.

Steps to Increase Salary

To increase your salary from the position of a Research Analyst, consider the following strategies:

• Skill Enhancement: Continuously update and expand your technical skills, especially in emerging AI/ML technologies and tools.
• Advanced Education: Pursue further education, such as a master's or Ph.D., which can open doors to higher-level positions.
• Networking: Build a strong professional network to learn about new opportunities and gain insights into industry trends.
• Performance Excellence: Consistently exceed performance expectations to position yourself for promotions and salary raises.
• Industry Transition: Consider moving to industries or companies known for higher pay scales, such as tech giants or financial firms.

Educational Requirements

Most Research Analyst positions in AI/ML/Data Science require at least a bachelor's degree in a related field such as Computer Science, Data Science, Statistics, or Mathematics. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex data analysis and model development. Advanced degrees can provide a deeper understanding of machine learning algorithms, statistical methods, and data management techniques, which are crucial for success in this field.

Helpful Certifications

While not always mandatory, certain certifications can enhance your qualifications and demonstrate your expertise to potential employers. 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 validate your skills in specific tools and platforms, making you a more attractive candidate for advanced roles.

Required Experience

Typically, employers look for candidates with at least 2-5 years of experience in data analysis, machine learning, or a related field. Experience with data manipulation, statistical analysis, and the development of predictive models is highly valued. Practical experience with programming languages such as Python or R, as well as familiarity with data visualization tools, is often required. Internships, research projects, or previous roles in data-centric positions can also contribute to the necessary experience.

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