Data Scientist Salary in United States during 2022

Salary details

The average Data Scientist salary lies between USD 129,300 and USD 185,900 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 Data Scientist roles

The three most common job tag items assiciated with Data Scientist job listings are Python, Machine Learning and SQL. 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 | 2740 jobs Machine Learning | 2364 jobs SQL | 2008 jobs Statistics | 1994 jobs Engineering | 1885 jobs R | 1484 jobs Computer Science | 1477 jobs Research | 1436 jobs Mathematics | 1182 jobs Testing | 908 jobs ML models | 849 jobs PhD | 688 jobs Spark | 659 jobs AWS | 654 jobs Data analysis | 620 jobs NLP | 611 jobs Pipelines | 611 jobs Tableau | 604 jobs Economics | 589 jobs Deep Learning | 549 jobs

Top 20 Job Perks/Benefits for Data Scientist roles

The three most common job benefits and perks assiciated with Data Scientist job listings are Career development, Health care and Startup environment. 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 | 2225 jobs Health care | 997 jobs Startup environment | 867 jobs Flex hours | 756 jobs Flex vacation | 660 jobs Team events | 608 jobs Equity / stock options | 566 jobs Parental leave | 519 jobs Competitive pay | 510 jobs Insurance | 474 jobs Salary bonus | 375 jobs Medical leave | 363 jobs Wellness | 349 jobs 401(k) matching | 281 jobs Home office stipend | 259 jobs Conferences | 215 jobs Unlimited paid time off | 170 jobs Fitness / gym | 156 jobs Snacks / Drinks | 96 jobs Gear | 95 jobs

Salary Composition

In the United States, the salary composition for a Data Scientist can vary significantly based on region, industry, and company size. Typically, the salary package includes a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies.

• Region: Salaries tend to be higher in tech hubs like San Francisco, New York, and Seattle due to the higher cost of living and competition for talent. In these areas, the base salary might constitute around 70-80% of the total compensation, with bonuses and stock options making up the rest.

• Industry: Data Scientists in finance or tech industries often receive higher bonuses compared to those in academia or non-profits. In finance, bonuses can be a significant part of the compensation, sometimes up to 30-40% of the total package.

• Company Size: Larger companies may offer more comprehensive benefits and stock options, while startups might offer lower base salaries but higher equity stakes.

Increasing Salary

To increase your salary from a Data Scientist position, consider the following strategies:

• Specialization: Develop expertise in high-demand areas such as deep learning, natural language processing, or big data technologies. Specializing can make you more valuable and justify a higher salary.

• Leadership Roles: Transitioning into a leadership or managerial role can significantly increase your earning potential. This might involve leading a team of data scientists or managing cross-functional projects.

• Continuous Learning: Stay updated with the latest tools and technologies in AI/ML. Attending workshops, conferences, and pursuing advanced certifications can enhance your skills and marketability.

• Networking: Building a strong professional network can open up opportunities for higher-paying positions. Engage with industry groups, attend meetups, and connect with peers on platforms like LinkedIn.

Educational Requirements

Most Data Scientist roles require at least a bachelor's degree in a related field such as computer science, statistics, mathematics, or engineering. However, a master's degree or Ph.D. is often preferred, especially for positions involving complex data analysis or research. Advanced degrees can provide a deeper understanding of machine learning algorithms, statistical methods, and data modeling, which are crucial for high-level data science roles.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise:

• Certified Analytics Professional (CAP): This certification is recognized across industries and validates your ability to transform data into valuable insights.

• Google Professional Data Engineer: This certification focuses on designing, building, and operationalizing data processing systems, which is highly relevant for data scientists working with big data.

• AWS Certified Machine Learning – Specialty: This certification is beneficial for those working with machine learning models on the AWS platform.

Experience Requirements

Typically, employers look for candidates with 2-5 years of experience in data science or related fields. Experience with data analysis, statistical modeling, and machine learning is crucial. Additionally, hands-on experience with programming languages like Python or R, and tools like TensorFlow, PyTorch, or Hadoop, is often required. Experience in a specific industry can also be advantageous, as it provides domain knowledge that can be critical for certain roles.

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