Salary for Mid-level / Intermediate Decision Scientist during 2023

Salary details

The average mid-level / intermediate Decision Scientist salary lies between USD 142,200 and USD 204,500 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. 24, 2024

Salary trend

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

The three most common job tag items assiciated with mid-level / intermediate Decision 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 | 2 jobs Machine Learning | 2 jobs SQL | 2 jobs Engineering | 2 jobs Banking | 2 jobs Statistics | 2 jobs R | 1 jobs Deep Learning | 1 jobs ANN | 1 jobs Economics | 1 jobs Consulting | 1 jobs Data pipelines | 1 jobs Testing | 1 jobs FinTech | 1 jobs Business Analytics | 1 jobs Unstructured data | 1 jobs ML models | 1 jobs Pipelines | 1 jobs Credit risk | 1 jobs Mathematics | 1 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate Decision Scientist job listings are Health care, Career development and Insurance. 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:

Health care | 2 jobs Career development | 2 jobs Insurance | 2 jobs Salary bonus | 1 jobs

Salary Composition

The salary for a Mid-level/Intermediate Decision Scientist typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or benefits. The base salary is often the largest component, accounting for approximately 70-80% of the total compensation package. Performance bonuses can vary significantly depending on the company and industry, ranging from 10-20% of the total salary. Additional remuneration, such as stock options, profit-sharing, or benefits like health insurance and retirement plans, can make up the remaining 5-10%.

Regional differences also play a role; for instance, salaries in tech hubs like Silicon Valley or New York City tend to be higher due to the cost of living and competitive job market. Industry-wise, tech companies and financial services often offer higher compensation compared to academia or non-profit sectors. Larger companies may provide more comprehensive benefits and stock options, while smaller companies might offer higher base salaries to attract talent.

Increasing Salary

To increase your salary from a Mid-level/Intermediate Decision Scientist position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging technologies and methodologies in AI/ML and data science. Specializing in niche areas like deep learning, natural language processing, or big data analytics can make you more valuable.

• Advanced Education: Pursuing further education, such as a master's or Ph.D., can open doors to higher-level positions and salary brackets.

• Networking: Building a strong professional network can lead to opportunities in higher-paying roles or industries. Attend conferences, join professional organizations, and engage in online forums.

• Performance and Leadership: Demonstrating exceptional performance and taking on leadership roles in projects can position you for promotions and salary increases.

• Negotiation: When offered a new position or during performance reviews, negotiate your salary and benefits package. Research industry standards to make informed requests.

Educational Requirements

Most Mid-level/Intermediate Decision Scientist roles 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. Some positions may also require or prefer candidates with a Ph.D., especially in research-intensive roles or industries.

Helpful Certifications

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

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• Google Professional Machine Learning Engineer: Demonstrates proficiency in designing, building, and productionizing ML models.
• AWS Certified Machine Learning – Specialty: Shows expertise in using AWS for machine learning solutions.
• Microsoft Certified: Azure AI Engineer Associate: Validates skills in using Azure for AI solutions.

Required Experience

Typically, a Mid-level/Intermediate Decision Scientist is expected to have 3-5 years of relevant experience. This experience should include hands-on work with data analysis, machine learning model development, and statistical methods. Experience in a specific industry can also be beneficial, as it provides domain knowledge that can enhance decision-making processes.

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