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Computer Science Statistics Jobs (NOW HIRING)

VTG

Data Scientist

Mclean, VA · On-site

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field (PhD preferred for some roles) * 5+ years of experience in data science or a related field

Cmu

Senior Data Scientist

Arlington, VA · On-site

Requirements: * BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with ten (10) years of experience or equivalent combination of training ...

VTG

Data Scientist

Chantilly, VA

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field (PhD preferred for some roles) * 5+ years of experience in data science or a related field

Cmu

Associate Data Scientist

Pittsburgh, PA · On-site

$57K - $57K/yr

Requirements: * BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with three (3) years of experience or equivalent combination of training ...

VTG

Data Scientist with Security Clearance

Chantilly, VA · On-site

$105K - $215K/yr

Bachelor's Degree in Data Science, Statistics, Mathematics, Computer Science, or related field * Preferred Qualifications: Experience supporting federal, DoD, or IC programs, Exposure to mission ...

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Computer Science Statistics information

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$37.5K

$122.7K

$196.5K

How much do computer science statistics jobs pay per year?

As of Aug 13, 2026, the average yearly pay for computer science statistics in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

Do computer science statisticians make a lot of money?

Computer science statisticians typically earn competitive salaries, especially with advanced skills in data analysis, programming, and statistical software. Salaries vary based on experience, education, and location, but the field generally offers strong earning potential compared to many other roles in technology and data science.

What is a computer science statistics?

A Computer Science Statistics job involves applying statistical methods and data analysis techniques to solve problems in computing, artificial intelligence, and software development. Professionals in this field work with large datasets, develop predictive models, and optimize algorithms for machine learning, cybersecurity, and data science applications. They may work in industries such as finance, healthcare, or technology, using statistical reasoning to enhance decision-making and efficiency. Strong programming skills, knowledge of probability theory, and experience with data visualization are typically required.

What jobs do most computer science statistics majors get?

Computer science statistics majors often find employment as data analysts, data scientists, machine learning engineers, and software developers. These roles typically require skills in programming languages like Python or R, statistical analysis, and data visualization tools. Many positions are available in technology, finance, healthcare, and consulting industries.

Is statistics useful in computer science?

Statistics is highly useful in computer science, especially for data analysis, machine learning, and algorithm development. It provides essential tools for interpreting data, making predictions, and optimizing systems, which are core skills in many computer science roles.

What do computer science statistics professionals do?

Professionals in Computer Science Statistics roles frequently work on projects involving data analysis, predictive modeling, and the development of algorithms to extract insights from large datasets. Their typical responsibilities include cleaning and preparing data, designing and running statistical tests, coding custom analytics solutions, and visualizing results for reports or presentations. Collaboration with teams such as data engineers, software developers, and business analysts is common to ensure that statistical models effectively address real-world business problems. This role offers opportunities to work across diverse industries, allowing for continual learning and skill development.

What skills and qualifications are needed for computer science statistics?

To excel in a Computer Science Statistics role, a strong background in both statistical analysis and computer science principles, usually backed by a degree in a related field, is essential. Expertise in programming languages like Python or R, experience with statistical software, and familiarity with databases or machine learning libraries are highly valued. Analytical thinking, attention to detail, and effective communication are key soft skills that differentiate top performers in this position. Mastery of these skills enables professionals to accurately interpret data, develop robust analytical solutions, and clearly convey complex findings to both technical and non-technical stakeholders.

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What cities are hiring for Computer Science Statistics jobs?

Cities with the most Computer Science Statistics job openings:

What are the most commonly searched types of Computer Science Statistics jobs?

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What states have the most Computer Science Statistics jobs?

States with the most job openings for Computer Science Statistics jobs include:

What job categories do people searching Computer Science Statistics jobs look for?

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Computer Science Statistics jobs near you
Infographic showing various Computer Science Statistics job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 80% Full Time, 14% Part Time, 3% Contract, and 1% Nights. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Data Scientist

VTG

Mclean, VA • On-site

Full-time

Re-posted 21 days ago

Job description

Overview

VTG is seeking a highly analytical and driven Data Scientist with at least 5 years of experience leveraging data to drive business insights and decision-making. The ideal candidate will have strong expertise in statistical analysis, machine learning, and data modeling, with the ability to translate complex data into actionable insights.


What will you do?
  • Analyze large, complex datasets to identify trends, patterns, and actionable insights
  • Develop, train, and validate machine learning and statistical models
  • Design and implement experiments, including A/B testing and predictive analytics
  • Collaborate with data engineers and analysts to ensure data quality and accessibility
  • Communicate findings and recommendations to technical and non-technical stakeholders
  • Build data visualizations and dashboards to present insights effectively
  • Deploy and monitor machine learning models in production environments
  • Continuously improve model performance and accuracy
  • Stay current with emerging data science techniques, tools, and technologies

Do you have what it takes?
  • Active TS/SCI with Polygraph required.
  • Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field (PhD preferred for some roles)
  • 5+ years of experience in data science or a related field
  • Strong proficiency in programming languages such as Python or R
  • Experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch)
  • Strong foundation in statistics, probability, and data analysis techniques
  • Experience with SQL and working with large datasets
  • Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn)
  • Familiarity with cloud platforms (AWS, Azure, or GCP)
Qualifications:
  • Active TS/SCI with Polygraph required.
  • Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field (PhD preferred for some roles)
  • 5+ years of experience in data science or a related field
  • Strong proficiency in programming languages such as Python or R
  • Experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch)
  • Strong foundation in statistics, probability, and data analysis techniques
  • Experience with SQL and working with large datasets
  • Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn)
  • Familiarity with cloud platforms (AWS, Azure, or GCP)
Education:UNAVAILABLEEmployment Type: FULL_TIME

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