Salary for Mid-level / Intermediate Data Scientist in United States during 2024

Salary details

The average mid-level / intermediate Data Scientist salary lies between USD 103,710 and USD 179,000 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: Jan. 19, 2025

Salary trend

Top 20 Job Tags for Mid-level / Intermediate Data Scientist roles

The three most common job tag items assiciated with mid-level / intermediate Data Scientist job listings are Python, Statistics and Machine Learning. 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:

Python | 3142 jobs Statistics | 2773 jobs Machine Learning | 2745 jobs SQL | 2425 jobs Engineering | 2162 jobs Computer Science | 1869 jobs R | 1861 jobs Mathematics | 1648 jobs Research | 1521 jobs Data analysis | 1261 jobs ML models | 1083 jobs Testing | 918 jobs AWS | 916 jobs Data visualization | 872 jobs Tableau | 793 jobs Pipelines | 767 jobs Spark | 733 jobs NLP | 718 jobs Big Data | 674 jobs Security | 673 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Data Scientist roles

The three most common job benefits and perks assiciated with mid-level / intermediate Data Scientist 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 | 2576 jobs Health care | 1342 jobs Equity / stock options | 893 jobs Flex hours | 885 jobs Competitive pay | 675 jobs Insurance | 629 jobs Startup environment | 619 jobs Medical leave | 617 jobs Parental leave | 570 jobs Team events | 539 jobs Salary bonus | 527 jobs Flex vacation | 515 jobs 401(k) matching | 400 jobs Wellness | 348 jobs Conferences | 159 jobs Unlimited paid time off | 140 jobs Flexible spending account | 136 jobs Relocation support | 119 jobs Fitness / gym | 113 jobs Transparency | 113 jobs

Salary Composition

The salary for a mid-level or intermediate data scientist in the United States typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. 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 profitability and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can be a significant part of the total compensation, especially in high-growth industries. Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job market.

Increasing Salary

To increase your salary from a mid-level data scientist position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging technologies and tools in AI/ML, such as deep learning frameworks, cloud computing, and big data technologies.
• Specialization: Develop expertise in a niche area within data science, such as natural language processing, computer vision, or reinforcement learning, which can make you more valuable to employers.
• Leadership Roles: Aim for roles that involve leading projects or teams, as managerial responsibilities often come with higher pay.
• Networking: Build a strong professional network through industry conferences, meetups, and online platforms like LinkedIn to learn about higher-paying opportunities.
• Advanced Education: Consider pursuing advanced degrees or certifications that can justify a higher salary.

Educational Requirements

Most mid-level data scientist positions require at least a bachelor's degree in a relevant field such as computer science, statistics, mathematics, or engineering. However, a master's degree is often preferred and can be a significant advantage. Degrees in data science or analytics are becoming increasingly common and are highly regarded. Some roles may also value interdisciplinary studies that combine technical skills with business acumen.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your commitment to the field. Some popular certifications include:

• Certified Analytics Professional (CAP)
• Google Professional Data Engineer
• Microsoft Certified: Azure Data Scientist Associate
• AWS Certified Machine Learning – Specialty
• TensorFlow Developer Certificate

These certifications can validate your skills in specific tools and platforms, making you more attractive to potential employers.

Required Experience

Typically, a mid-level data scientist is expected to have 3 to 5 years of relevant experience. This experience should include hands-on work with data analysis, machine learning model development, and deployment. Experience in handling real-world data problems, working with cross-functional teams, and delivering actionable insights is crucial. Familiarity with programming languages like Python or R, and tools like SQL, TensorFlow, or PyTorch, is often required.

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