Salary for Senior-level / Expert Decision Scientist in United States during 2024

Salary details

The average senior-level / expert Decision Scientist salary lies between USD 120,000 and USD 177,500 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 Senior-level / Expert Decision Scientist roles

The three most common job tag items assiciated with senior-level / expert Decision Scientist job listings are Statistics, SQL 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:

Statistics | 89 jobs SQL | 86 jobs Python | 85 jobs Mathematics | 73 jobs Engineering | 72 jobs Machine Learning | 67 jobs Tableau | 48 jobs Computer Science | 36 jobs GitHub | 35 jobs CX | 34 jobs Testing | 32 jobs Excel | 32 jobs Spark | 31 jobs Economics | 31 jobs R | 29 jobs Hadoop | 27 jobs NLP | 26 jobs Causal inference | 22 jobs Data analysis | 21 jobs Research | 19 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Decision Scientist roles

The three most common job benefits and perks assiciated with senior-level / expert Decision Scientist job listings are Competitive pay, Career development 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:

Competitive pay | 48 jobs Career development | 46 jobs Equity / stock options | 39 jobs Team events | 37 jobs Health care | 34 jobs Flex hours | 22 jobs Insurance | 22 jobs Salary bonus | 21 jobs Flex vacation | 19 jobs 401(k) matching | 14 jobs Startup environment | 14 jobs Parental leave | 9 jobs Flexible spending account | 8 jobs Wellness | 6 jobs Medical leave | 5 jobs Signing bonus | 4 jobs Snacks / Drinks | 4 jobs Transparency | 3 jobs Conferences | 2 jobs Home office stipend | 2 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Decision Scientist typically includes a combination of a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the majority of the total compensation package, ranging from 70% to 85%. Bonuses can vary significantly depending on the company and industry, often ranging from 10% to 20% of the base salary. Additional remuneration, such as stock options, can be a significant part of the package in tech startups or large tech firms, sometimes accounting for 5% to 15% of the total compensation.

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 markets. Industry-wise, tech and finance sectors often offer higher compensation compared to healthcare or manufacturing. Company size can also influence salary composition, with larger companies typically offering more comprehensive bonus structures and stock options.

Increasing Salary Further

To increase your salary beyond the median of USD 145,000, consider the following strategies:

• Specialization: Develop expertise in a niche area of AI/ML or data science that is in high demand, such as deep learning, natural language processing, or AI ethics.
• Leadership Roles: Transition into leadership or managerial roles, such as a Director of Data Science or Chief Data Officer, which typically offer higher salaries.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML. Pursuing advanced certifications or a Ph.D. can also enhance your qualifications.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher compensation during job offers or performance reviews.

Educational Requirements

Most Senior-level Decision Scientist roles require at least a master's degree in a relevant field such as Computer Science, Statistics, Mathematics, or Data Science. A Ph.D. is often preferred, especially for roles that involve complex research and development tasks. The educational background should provide a strong foundation in statistical analysis, machine learning algorithms, and data manipulation techniques.

Helpful Certifications

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

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• TensorFlow Developer Certificate: Demonstrates proficiency in building and deploying machine learning models using TensorFlow.
• AWS Certified Machine Learning – Specialty: Shows expertise in implementing machine learning solutions on the AWS platform.
• Data Science Council of America (DASCA) Certifications: Offers various levels of data science certifications that are recognized globally.

Required Experience

Typically, a Senior-level Decision Scientist is expected to have at least 5 to 10 years of experience in data science or related fields. This experience should include hands-on work with data analysis, machine learning model development, and deployment. Experience in leading projects, mentoring junior team members, and collaborating with cross-functional teams is also highly valued.

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