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Full Time Data Science Engineer Jobs (NOW HIRING)

The Cyber Data Science Engineer provides support to the customer in the area of Cyber Security. Daily Tasks include, but are not limited to: * Utilize analytical, statistical, and programming skills ...

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Full Time Data Science Engineer information

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$44.5K

$129.7K

$177.5K

How much do full time data science engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for full time data science engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What is the difference between Full Time Data Science Engineer vs Data Analyst?

AspectFull Time Data Science EngineerData Analyst
Required CredentialsBachelor's or Master's in Data Science, Computer Science, or related fields; programming skills in Python, R; knowledge of machine learningBachelor's in Statistics, Mathematics, or related fields; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentDeveloping models, algorithms, and deploying data solutions in tech or enterprise settingsInterpreting data, creating reports, and supporting decision-making in various industries
Employer & Industry UsageTech companies, finance, healthcare, and e-commerceRetail, marketing, finance, and healthcare sectors

Full Time Data Science Engineers focus on building and deploying machine learning models and advanced data solutions, requiring programming and technical expertise. Data Analysts primarily interpret data, generate reports, and support business decisions with less emphasis on coding or model deployment. Both roles are essential but differ in technical depth and responsibilities.

Are full time data science engineers still in demand?

Full time data science engineers are currently in high demand across various industries due to the increasing reliance on data-driven decision making and AI technologies. Skills in programming, statistical analysis, and machine learning tools like Python, R, and SQL are highly valued, and many organizations seek professionals with these competencies for ongoing projects.
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What cities are hiring for Full Time Data Science Engineer jobs?

Cities with the most Full Time Data Science Engineer job openings:

What are the most commonly searched types of Data Science Engineer jobs?

The most popular types of Data Science Engineer jobs are:

What states have the most Full Time Data Science Engineer jobs?

States with the most job openings for Full Time Data Science Engineer jobs include:

Infographic showing various Full Time Data Science Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Cyber Data Science Engineer

RDR Inc

Chantilly, VA • On-site

Full-time

Re-posted 11 days ago


Job description

Description:

This position is contingent upon award.


Requires an active TS/SCI with CI Poly clearance prior to consideration.


Program Description:

The program provides Systems Engineering and Technical Assistance (SETA) core and non-core support in the areas of Cyber Security and Management to improve the Information Assurance (IA) posture of a National customer. The contracts Core Capabilities are: IA Management, Federal Information Security Management Act (FISMA) coordination and reporting, Risk Management Framework (RMF) application, IA compliance measurements and metrics, Assessment and Authorization (A&A), Vulnerability Management, and Cyber Defense support.


Position Description:

The Cyber Data Science Engineer provides support to the customer in the area of Cyber Security. Daily Tasks include, but are not limited to:

  • Utilize analytical, statistical, and programming skills to collect, analyze, and interpret large cybersecurity data sets
  • Develop data-driven solutions
  • Analyze data sets found in the customer's vulnerability scanning, authorization, and configuration management tools
  • Import and transform data into usable sets for analysis tools used by the customer (e.g., Tableau)
  • Provide analysis and graphical presentations of collected metrics for IA compliance status reporting
  • Support legacy visualization and situational awareness tools based on Microsoft Excel
  • Collaborate with the Heat Map team to investigate options to simplify and automate the current Heat Map


Requirements:

Current U.S. Government Top Secret clearance with SCI eligibility with favorably adjudicated Polygraph.

  • Bachelor of Science Degree in Science, Technology, Engineering or Mathematics (STEM) or an advanced IA certification (i.e., CISSP or CASP)
  • DoD 8570 certification in IAT or IAM
  • Deep understanding of statistics and analysis
  • Skilled in artificial intelligence and machine learning (e.g., SageMaker)
  • Ability to code in multiple languages, including Python
  • Knowledge of databases, data structures, and data architectures
  • Excellent communications skills – both verbal and non-verbal
  • Office Automation Skills – MS Office, MS Project, Visio
  • Self-starter requiring limited direction and supervision
  • Strong attention to detail
  • Ability to work in a team environment
  • Experience with data visualization tools (e.g. Tableau, Infogram, Chartbloks)
  • Experience with data transformation (structured data format/schema transformation) using common programming tools (e.g., Python, JSON, etc.)
  • Experience applying statistical analysis to large data sets

Desired:

  • Experience briefing senior customer personnel
  • Experience with Tableau administration
  • Ability to organize and prioritize numerous customer requests in a fast pace deadline driven environment
  • Familiarity with Amazon Web Services (AWS)
  • Familiarity with customer's IA processes
  • Experience with ServiceNow and Splunk
  • Experience supporting IC or DoD in the Cyber Security Domain
  • Familiarity with the RMF process
  • Experience with Relational Database Management System (RDMS)
  • Experience with Apache Hadoop and the Hadoop Distributed File System
  • Experience with Amazon Elastic MapReduce (EMR) and SageMaker
  • Experience with Machine Learning or Artificial Intelligence