Salary for Entry-level / Junior Data Scientist in United States during 2023

Salary details

The average entry-level / junior Data Scientist salary lies between USD 73,100 and USD 133,000 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 SQL. 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:

Python | 508 jobs Machine Learning | 426 jobs SQL | 309 jobs Statistics | 304 jobs R | 288 jobs Engineering | 268 jobs Computer Science | 236 jobs Mathematics | 205 jobs Research | 177 jobs Big Data | 135 jobs Data analysis | 121 jobs ML models | 110 jobs Deep Learning | 101 jobs TensorFlow | 100 jobs Testing | 96 jobs Pandas | 91 jobs Agile | 91 jobs NLP | 90 jobs R&D | 88 jobs PyTorch | 84 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, Health care and Flex hours. 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 | 350 jobs Health care | 141 jobs Flex hours | 133 jobs Startup environment | 127 jobs Competitive pay | 95 jobs Team events | 89 jobs Insurance | 84 jobs Flex vacation | 74 jobs Equity / stock options | 72 jobs Salary bonus | 50 jobs Parental leave | 47 jobs Medical leave | 41 jobs 401(k) matching | 33 jobs Conferences | 24 jobs Wellness | 16 jobs Home office stipend | 15 jobs Gear | 14 jobs Relocation support | 13 jobs Fitness / gym | 12 jobs Lunch / meals | 11 jobs

Salary Composition

The salary for an entry-level or junior data scientist in the United States typically consists of a base salary, performance bonuses, and sometimes 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. Performance bonuses can vary significantly depending on the company and individual performance, often ranging from 5% to 15% of the base salary. Additional remuneration might include stock options, especially in tech companies or startups, and comprehensive benefits packages that cover health insurance, retirement plans, and other perks.

The composition of the salary can vary based on several factors:

• Region: Salaries tend to be higher in tech hubs like San Francisco, New York, and Seattle due to the higher cost of living and competitive job markets.
• Industry: Industries such as finance, technology, and healthcare often offer higher salaries compared to education or non-profit sectors.
• Company Size: Larger companies may offer more comprehensive benefits and bonuses, while startups might offer equity as part of the compensation package.

Increasing Salary

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

• Skill Development: Continuously improve your technical skills, such as programming in Python or R, machine learning, and data visualization. Mastery of tools like TensorFlow, PyTorch, or Tableau can make you more valuable.
• Advanced Education: Pursuing a master's degree or specialized certifications can enhance your qualifications and open up higher-paying opportunities.
• Networking: Build a strong professional network by attending industry conferences, joining relevant online communities, and connecting with peers and mentors.
• Performance Excellence: Consistently exceed performance expectations and take on challenging projects to demonstrate your value to the organization.
• Negotiation: When the opportunity arises, negotiate your salary based on your contributions, market research, and industry standards.

Educational Requirements

Most entry-level data scientist positions require at least a bachelor's degree in a related field such as computer science, statistics, mathematics, or engineering. However, a master's degree in data science or a related discipline is increasingly preferred by employers, as it provides a deeper understanding of advanced analytical techniques and tools.

Helpful Certifications

While not always required, certain certifications can enhance your resume and demonstrate your expertise:

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• Google Data Analytics Professional Certificate: Offers foundational skills in data analysis.
• Microsoft Certified: Azure Data Scientist Associate: Focuses on using Azure to build and deploy machine learning models.
• AWS Certified Machine Learning – Specialty: Demonstrates your ability to design, implement, and maintain machine learning solutions on AWS.

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 analysis, programming, and machine learning projects is highly valued. Demonstrating your ability to work with real-world data and solve business problems can set you apart from other candidates.

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