Salary for Entry-level / Junior Applied Scientist in United States during 2024

Salary details

The average entry-level / junior Applied Scientist salary lies between USD 104,000 and USD 168,150 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 Applied Scientist roles

The three most common job tag items assiciated with entry-level / junior Applied Scientist job listings are Machine Learning, Research and Python. 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:

Machine Learning | 50 jobs Research | 50 jobs Python | 43 jobs Computer Science | 43 jobs Engineering | 39 jobs Deep Learning | 38 jobs Statistics | 34 jobs PhD | 31 jobs NLP | 25 jobs LLMs | 24 jobs PyTorch | 22 jobs Computer Vision | 20 jobs Java | 20 jobs TensorFlow | 17 jobs ML models | 15 jobs Data Mining | 13 jobs Mathematics | 13 jobs GitHub | 11 jobs Econometrics | 10 jobs EMNLP | 10 jobs

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

The three most common job benefits and perks assiciated with entry-level / junior Applied Scientist job listings are Career development, Conferences and Medical leave. 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 | 52 jobs Conferences | 27 jobs Medical leave | 26 jobs Flex hours | 23 jobs Health care | 17 jobs Startup environment | 17 jobs Flex vacation | 15 jobs Equity / stock options | 14 jobs Parental leave | 14 jobs Competitive pay | 13 jobs Team events | 7 jobs 401(k) matching | 6 jobs Insurance | 5 jobs Flexible spending account | 5 jobs Transparency | 3 jobs Home office stipend | 3 jobs Salary bonus | 2 jobs Wellness | 1 jobs Gear | 1 jobs Signing bonus | 1 jobs

Salary Composition for Entry-Level/Junior Applied Scientist Roles

The salary for an entry-level or junior applied scientist in AI/ML/Data Science typically consists of a base salary, performance 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. Performance bonuses can vary significantly depending on the company’s policies and individual performance metrics. Additional remuneration might include stock options, especially in tech companies, and benefits like health insurance, retirement plans, and sometimes relocation assistance. The composition can vary by region, with tech hubs like Silicon Valley offering higher base salaries and more lucrative stock options compared to other regions. Industry also plays a role; for instance, finance and tech industries often offer higher compensation packages compared to academia or non-profits. Company size can influence the package as well, with larger companies typically offering more comprehensive benefits and bonuses.

Steps to Increase Salary from an Entry-Level Position

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

• Skill Enhancement: Continuously upgrade your skills in AI/ML through online courses, workshops, and certifications. Specializing in high-demand areas like deep learning, natural language processing, or computer vision can make you more valuable.

• Networking: Build a strong professional network by attending industry conferences, meetups, and joining relevant online communities. Networking can open up opportunities for higher-paying positions.

• Performance Excellence: Consistently exceed performance expectations in your current role. Demonstrating your ability to deliver results can lead to promotions and salary increases.

• Advanced Education: Consider pursuing a master’s or Ph.D. in a related field. Advanced degrees can lead to higher-level positions and increased salary potential.

• Explore Opportunities: Keep an eye on job openings and be open to switching companies if a better opportunity arises. Sometimes, moving to a new company can result in a significant salary increase.

Educational Requirements for Entry-Level/Junior Applied Scientist Roles

Most entry-level or junior applied scientist positions require at least a bachelor’s degree in a relevant field such as computer science, data science, mathematics, statistics, or engineering. However, many employers prefer candidates with a master’s degree or even a Ph.D., especially for roles that involve complex problem-solving and research. Coursework in machine learning, data analysis, and programming is highly beneficial. Additionally, having a strong foundation in mathematics and statistics is crucial for understanding and developing machine learning models.

Helpful Certifications for Aspiring Applied Scientists

While not always mandatory, certain certifications can enhance your resume and demonstrate your expertise in AI/ML. Some popular certifications include:

• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• IBM Data Science Professional Certificate

These certifications can validate your skills and knowledge, making you a more competitive candidate in the job market.

Experience Requirements for Entry-Level/Junior Roles

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. Experience with programming languages such as Python or R, and familiarity with machine learning frameworks like TensorFlow or PyTorch, is often required. While extensive professional experience is not expected, demonstrating hands-on experience through personal projects, contributions to open-source projects, or participation in hackathons can be advantageous.

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