Salary for Entry-level / Junior Data Scientist in United States during 2022

Salary details

The average entry-level / junior Data Scientist salary lies between USD 80,000 and USD 130,000 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

Salary trend

Top 20 Job Tags for Entry-level / Junior Data Scientist roles

The three most common job tag items assiciated with entry-level / junior Data Scientist job listings are Python, Machine Learning and Statistics. Below you find a list of the 20 most occuring job tags in 2022 and the number of open jobs that where associated with them during that period:

Python | 171 jobs Machine Learning | 146 jobs Statistics | 105 jobs Engineering | 100 jobs SQL | 90 jobs R | 84 jobs Mathematics | 79 jobs Computer Science | 76 jobs Research | 65 jobs Pandas | 47 jobs Deep Learning | 46 jobs Big Data | 45 jobs ML models | 45 jobs NumPy | 39 jobs TensorFlow | 37 jobs Data analysis | 37 jobs AWS | 35 jobs Scikit-learn | 33 jobs Spark | 33 jobs NLP | 32 jobs

Top 20 Job Perks/Benefits for Entry-level / Junior Data Scientist roles

The three most common job benefits and perks assiciated with entry-level / junior Data Scientist job listings are Career development, Startup environment and Flex hours. Below you find a list of the 20 most occuring job perks or benefits in 2022 and the number of open jobs that where offering them during that period:

Career development | 119 jobs Startup environment | 52 jobs Flex hours | 38 jobs Health care | 33 jobs Team events | 32 jobs Competitive pay | 27 jobs Flex vacation | 21 jobs Equity / stock options | 19 jobs Insurance | 16 jobs Conferences | 11 jobs Salary bonus | 10 jobs Snacks / Drinks | 8 jobs Parental leave | 7 jobs Wellness | 7 jobs Medical leave | 7 jobs Home office stipend | 6 jobs Gear | 5 jobs 401(k) matching | 4 jobs Lunch / meals | 4 jobs Relocation support | 4 jobs

Salary Composition

The salary for an entry-level or junior data scientist in the United States typically consists of a base salary, potential 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 and industry. For instance, tech companies and startups might offer performance-based bonuses or stock options as part of their compensation packages. In contrast, more traditional industries might offer smaller bonuses. The region also plays a crucial role; for example, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and demand for talent. Company size can influence salary composition as well, with larger companies often providing more comprehensive benefits and bonuses compared to smaller firms.

Increasing Salary

To increase your salary from an entry-level position, consider gaining specialized skills or certifications that are in high demand, such as expertise in machine learning algorithms, data engineering, or big data technologies. Pursuing a master's degree or further education in data science or a related field can also enhance your qualifications. Additionally, gaining experience in a specific industry, such as finance or healthcare, can make you more valuable to employers in those sectors. Networking and building a strong professional presence can lead to opportunities for advancement or higher-paying roles. Finally, consider seeking roles in regions or companies known for higher compensation, or negotiating your salary based on market research and your growing expertise.

Educational Requirements

Most entry-level data scientist positions require at least a bachelor's degree in a relevant field such as computer science, statistics, mathematics, or engineering. However, many employers prefer candidates with a master's degree in data science or a related discipline. Coursework in machine learning, data analysis, and programming languages like Python or R is often essential. Some positions may also require knowledge of databases and data visualization tools.

Helpful Certifications

While not always mandatory, certain certifications can enhance your resume and demonstrate your commitment to the field. Popular certifications include the Certified Analytics Professional (CAP), Microsoft Certified: Azure Data Scientist Associate, and the Google Professional Data Engineer. These certifications can validate your skills in data analysis, machine learning, and cloud computing, making you a more competitive candidate.

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 data manipulation, statistical analysis, and machine learning projects is often expected. Familiarity with tools like SQL, Python, R, and data visualization software is also beneficial. While extensive professional experience is not required, demonstrating your ability to apply theoretical knowledge to real-world problems can set you apart.

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