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Mid Level Bayesian Statistics Jobs (NOW HIRING)

Beyond SOF

System engineer - Mid Level

Springfield, VA · On-site

System Engineer - Mid Level Position Description: Product quality SYSTEM ENGINEER will lead the ... They will lead a team of image scientists, image analysts, photogrammetrists, and statisticians to ...

Wiser

Human Geographer (Mid-Level)- TS/SCI

Springfield, VA · On-site

$85K - $110K/yr

Human Geographer - Mid-Level - TS/SCI Location: Springfield, VA Experience Level: Level 3, Middle ... statistical data into tables compatible with ArcGIS, participating in quality control checks ...

Varsity Tutors

Statistics Graduate Level Tutor

NM · Remote

$18 - $40/hr

... Bayesian inference, regression analysis, multivariate methods, experimental design, and ... level statistical analysis. * Conceptual Teaching & Problem-Solving: Skilled at breaking down ...

Varsity Tutors

Statistics Graduate Level Tutor

WI · Remote

$18 - $40/hr

... Bayesian inference, regression analysis, multivariate methods, experimental design, and ... level statistical analysis. * Conceptual Teaching & Problem-Solving: Skilled at breaking down ...

Varsity Tutors

Statistics Graduate Level Tutor

OK · Remote

$18 - $40/hr

... Bayesian inference, regression analysis, multivariate methods, experimental design, and ... level statistical analysis. * Conceptual Teaching & Problem-Solving: Skilled at breaking down ...

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Mid Level Bayesian Statistics information

What can you do with Bayesian statistics?

A mid-level Bayesian statistics professional can apply Bayesian methods to model uncertainty, update probabilities with new data, and improve decision-making processes across various fields such as healthcare, finance, and technology. Proficiency in statistical software like R or Python and understanding of probabilistic programming are essential for implementing these techniques effectively.

Is Bayesian statistics difficult?

Bayesian statistics as a mid-level role involves understanding probability models, prior and posterior distributions, and using tools like R or Python for analysis. While it requires a solid grasp of statistical concepts and programming skills, the difficulty depends on prior experience with mathematics and data analysis. Consistent practice and formal training can help develop proficiency in this specialized area.

What job should I do if I like statistics?

A mid-level Bayesian statistician typically works in data analysis, research, or modeling roles across industries such as healthcare, finance, or technology. These roles involve applying statistical methods, programming skills in languages like R or Python, and understanding Bayesian inference to solve complex problems. Certification or advanced degrees in statistics or related fields can enhance job prospects.

What is the difference between Mid Level Bayesian Statistics vs Data Scientist?

AspectMid Level Bayesian StatisticsData Scientist
Required CredentialsMaster's or PhD in Statistics, Mathematics, or related fieldBachelor's or higher in Data Science, Computer Science, or related field
Work EnvironmentResearch-focused, analytical, often in finance, healthcare, or academiaCross-functional teams, data analysis, machine learning, business insights
Industry UsageStatistical modeling, probabilistic analysis, research projectsData analysis, predictive modeling, data visualization

Mid Level Bayesian Statistics specialists focus on advanced probabilistic modeling and statistical inference, often in research or specialized industries. Data Scientists have a broader scope, combining statistical analysis with programming and machine learning to solve business problems. While both roles require strong analytical skills, Bayesian statisticians typically emphasize probabilistic models, whereas Data Scientists integrate multiple techniques for data-driven decision-making.

What type of statistician makes the most money?

Senior-level statisticians, such as data science managers or quantitative research directors, tend to earn the highest salaries. Specializations in machine learning, Bayesian methods, or roles in finance and technology often command higher compensation, especially with advanced skills and relevant certifications.
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Mid Level Bayesian Statistics jobs near you
Infographic showing various Mid Level Bayesian Statistics job openings in the United States as of July 2026, with employment types broken down into 4% Locum Tenens, 53% As Needed, 2% Full Time, 26% Temporary, 14% Nights, and 1% Summer. Highlights an 67% Physical, 2% Hybrid, and 31% Remote job distribution.
System engineer - Mid Level

System engineer - Mid Level

Beyond SOF

Springfield, VA • On-site

Full-time

Re-posted 25 days ago

Job description

System Engineer - Mid Level
Position Description:
Product quality SYSTEM ENGINEER will lead the planning, test development, data definition, and task execution for new and existing products within the National System for Geospatial-Intelligence (NSG). The candidate will need to write clear test plans to satisfy the test objectives. They will lead a team of image scientists, image analysts, photogrammetrists, and statisticians to perform specific tasks, track issues, and clearly communicate status and results to multiple stakeholders. The qualified candidate should have experience with test design to verify and validate products against requirements to meet the planned concept of operations. The ideal candidate will have image science or imagery analysis experience or knowledge ready to apply to the challenges of the group.
Required Experience/Education:
  • Bachelor of Science (BS) degree in System Engineering, Electrical Engineering, Physics, Software Engineering, or a related Science or Engineering
  • 5-10 years of system engineering experience, including independent testing and data verification, requirements, and development of the concept of operations.
  • Experience with sensor imaging systems, products, and exploitation processes
  • Strong written and oral communication skills, with emphasis on the briefing, to obtain decisions and solve technical issues and test plans/report writing.
  • Ability to work independently as well as part of a team
  • Willingness to learn, solve problems and perform in a dynamic work environment
Preferred Skillset:
  • Experience in remote sensing phenomenologies (for example EO/IR/SAR)
  • Knowledge of NSG tasking, collection, processing, exploitation, and dissemination (TCPED) image chain
  • Experience with product quality assessments, visual or metadata assessments

Position Description:

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