Salary for Mid-level / Intermediate Associate during 2024

Salary details

The average mid-level / intermediate Associate salary lies between USD 90,000 and USD 170,000 globally. 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.

All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Nov. 10, 2024

Top 20 Job Tags for Mid-level / Intermediate Associate roles

The three most common job tag items assiciated with mid-level / intermediate Associate job listings are Python, Engineering and SQL. 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 | 2237 jobs Engineering | 1882 jobs SQL | 1632 jobs Machine Learning | 1470 jobs Computer Science | 1459 jobs Statistics | 1419 jobs Research | 1398 jobs R | 1032 jobs Mathematics | 954 jobs Testing | 890 jobs Data management | 841 jobs Data analysis | 826 jobs Agile | 793 jobs AWS | 763 jobs Security | 762 jobs Finance | 758 jobs Data Analytics | 749 jobs Excel | 747 jobs Tableau | 707 jobs Architecture | 688 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate Associate 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 2024 and the number of open jobs that where offering them during that period:

Career development | 2426 jobs Health care | 1079 jobs Flex hours | 990 jobs Team events | 733 jobs Competitive pay | 656 jobs Startup environment | 606 jobs Insurance | 494 jobs Flex vacation | 488 jobs Equity / stock options | 479 jobs Wellness | 467 jobs Parental leave | 402 jobs Salary bonus | 400 jobs Medical leave | 325 jobs Conferences | 215 jobs Relocation support | 215 jobs Transparency | 181 jobs 401(k) matching | 176 jobs Fitness / gym | 120 jobs Home office stipend | 74 jobs Unlimited paid time off | 67 jobs

Salary Composition

The salary for a mid-level AI/ML/Data Science role typically consists of a base salary, performance bonuses, and additional remuneration such as stock options or profit-sharing. 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 success and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration, like stock options, is more common in tech companies and startups, especially in regions like Silicon Valley. In larger corporations or financial sectors, bonuses might be more substantial, reflecting the company's profitability. Regional differences also play a role; for instance, salaries in major tech hubs like San Francisco or New York are generally higher than in other regions due to the cost of living and competitive job market.

Increasing Salary

To increase your salary from a mid-level position, consider pursuing advanced roles such as Senior Data Scientist, Machine Learning Engineer, or AI Specialist. This often requires gaining deeper expertise in specialized areas like deep learning, natural language processing, or big data analytics. Networking within the industry and seeking mentorship can provide insights into career advancement opportunities. Additionally, taking on leadership roles in projects or teams can demonstrate your capability to handle more responsibility, which is often rewarded with higher pay. Continuous learning and staying updated with the latest technologies and methodologies in AI/ML can also make you more valuable to your employer.

Educational Requirements

Most mid-level AI/ML/Data Science 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 or Ph.D. is often preferred, especially for roles that involve complex problem-solving and research. These advanced degrees provide a deeper understanding of algorithms, data structures, and statistical models, which are crucial for developing effective AI solutions. Some positions may also value interdisciplinary knowledge, such as combining computer science with domain-specific expertise.

Helpful Certifications

Certifications can enhance your credentials and demonstrate your commitment to the field. Some valuable certifications include:

• Certified Data Scientist (CDS): Offered by various institutions, this certification covers essential data science skills and tools.
• TensorFlow Developer Certificate: Validates your ability to build and deploy machine learning models using TensorFlow.
• AWS Certified Machine Learning – Specialty: Focuses on designing and implementing machine learning solutions on the AWS platform.
• Microsoft Certified: Azure AI Engineer Associate: Demonstrates proficiency in using Azure AI services to build and integrate AI solutions.

These certifications can help differentiate you from other candidates and may lead to better job opportunities and salary prospects.

Required Experience

Typically, a mid-level position requires 3 to 5 years of experience in data science, machine learning, or a related field. This experience should include hands-on work with data analysis, model development, and deployment. Familiarity with programming languages such as Python or R, and tools like TensorFlow, PyTorch, or Scikit-learn, is often expected. Experience in handling large datasets and working with cloud platforms like AWS, Azure, or Google Cloud can also be advantageous.

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