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Bayesian Modeling Jobs in Chicago, IL (NOW HIRING)

Sr Demand Planner

Bolingbrook, IL · On-site

$102K - $125K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

Proven track record of driving demand planning improvements and optimizing inventory strategies, knowledge of demand forecasting models ( e.g., Time Series, Bayesian, etc.) * Advanced proficiency in ...

Statistician III

Chicago, IL · Hybrid

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... modeling, machine learning methods, data linkage, statistical matching, statistical disclosure limitation, small area estimation, Bayesian analysis, assessing data quality, data visualization for ...

Statistician III

Chicago, IL · On-site

$130K - $140K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... modeling, machine learning methods, data linkage, statistical matching, statistical disclosure limitation, small area estimation, Bayesian analysis, assessing data quality, data visualization for ...

Statistician III

Chicago, IL · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... modeling, machine learning methods, data linkage, statistical matching, statistical disclosure limitation, small area estimation, Bayesian analysis, assessing data quality, data visualization for ...

Showing results 41-53

Bayesian Modeling information

See Chicago, IL salary details

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How much do bayesian modeling jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for bayesian modeling in Chicago, IL is $60.48, according to ZipRecruiter salary data. Most workers in this role earn between $54.23 and $70.34 per hour, depending on experience, location, and employer.

What is the difference between Bayesian Modeling vs Data Scientist?

AspectBayesian ModelingData Scientist
Required CredentialsStatistics, Mathematics, Data AnalysisStatistics, Computer Science, Data Analysis
Work EnvironmentResearch-focused, statistical modelingCross-functional, data analysis, visualization
Industry UsageResearch, academia, specialized analyticsBusiness, tech, finance, healthcare
Common Search/ComparisonYesYes

Bayesian Modeling and Data Scientists often overlap in skills like statistics and data analysis. Bayesian Modeling specializes in probabilistic models and statistical inference, while Data Scientists have broader roles including data cleaning, visualization, and machine learning. Both roles are essential in data-driven industries, but Bayesian Modeling is more focused on advanced statistical techniques.

What are the key skills and qualifications needed to thrive as a Bayesian modeler, and why are they important?

To thrive as a Bayesian Modeler, you need a solid background in statistics, probability theory, and mathematical modeling, often supported by an advanced degree in statistics, mathematics, or a related field. Proficiency with programming languages such as R, Python, or Stan, and experience with statistical software and Bayesian inference tools are essential. Strong analytical thinking, attention to detail, and effective communication skills help in interpreting results and collaborating with multidisciplinary teams. These skills ensure accurate model development, reliable data-driven insights, and clear communication of complex findings to stakeholders.

How does a Bayesian modeling specialist typically collaborate with cross-functional teams in a workplace setting?

Bayesian Modeling specialists often work closely with data scientists, software engineers, and domain experts to integrate probabilistic models into larger analytical or production systems. They are involved in translating complex statistical concepts into actionable insights and recommendations tailored to business needs. Effective communication is key, as they must present findings to both technical and non-technical stakeholders, ensuring that model assumptions and results are clearly understood. Collaboration may also include contributing to code reviews, sharing best practices for model validation, and mentoring colleagues on Bayesian methodologies.

What is Bayesian modeling?

Bayesian modeling is a statistical approach that uses Bayes' Theorem to update the probability of a hypothesis as more data becomes available. It incorporates prior beliefs or knowledge, combines them with observed data, and produces a posterior probability distribution to guide inference and decision-making. This approach is widely used in various fields such as machine learning, data science, and scientific research for tasks like parameter estimation, prediction, and model selection.

What cities near Chicago, IL are hiring for Bayesian Modeling jobs?

Cities near Chicago, IL with the most Bayesian Modeling job openings:

Senior Biostatistician

Loyola University Chicago

Chicago, IL • On-site

Full-time

Re-posted 7 days ago


Job description

Position Details
Position Details
Job Title
Sr. Biostatistician
Position Number
8151034
Work Modality
Fully Remote Work
Is this request for the creation of a new Position (or the modification of an existing Position) to temporarily support the WorkDay ERP?
No
Job Category
University Staff
Job Type
Full-Time
FLSA Status
Exempt
Campus
Maywood-Health Sciences Campus
Department Name
PUBLIC HEALTH SCIENCES
Location Code
PUBLIC HEALTH SCIENCES (06250A)
Is this split and/or fully grant funded?
Yes
Duties and Responsibilities
We have an immediate opening for a Senior Biostatistician position in Dr. Qeadan's research team in the Public Health Sciences Department within the Parkinson School of Health Sciences and Public Health. We are seeking an experienced biostatistician with expertise in electronic health record (EHR) data, advanced statistical methods, and SAS and R programming to lead and support clinical and public health research projects. This role involves providing statistical leadership in study design, EHR data management and analysis, manuscript preparation, grant development, and collaborative research initiatives.
Training and Experience:
  • Demonstrated experience serving as the lead biostatistician on research studies and multidisciplinary projects.
  • Required experience working directly with electronic health record (EHR) data, including extraction, transformation, cleaning, validation, and creation of research-ready analytic datasets.
  • Experience developing patient cohorts, derived variables, and computable phenotypes using diagnosis, procedure, laboratory, medication, and encounter data.
  • Experience supporting observational research using EHR-derived real-world data (RWD), clinical data warehouses, or healthcare data repositories.
  • Experience mentoring and providing methodological guidance to biostatisticians, analysts, researchers, and trainees.

Statistical Expertise
Formal training in probability theory, mathematical statistics, linear models, and categorical data analysis. Expertise in multiple advanced statistical methodologies, including several of the following:
  • Survival analysis
  • Hierarchical and mixed-effects models
  • Clinical trial design and analysis
  • Structural equation modeling
  • Bayesian data analysis
  • Multivariate statistical methods
  • Longitudinal data analysis
  • Causal inference methods
  • Demonstrated ability to select and apply appropriate statistical methodologies to complex clinical, public health, and observational research questions.

Technical Skills
  • Advanced proficiency in SAS and R, including development of custom SAS macros, R functions, and automated analytical workflows.
  • Demonstrated ability to develop well-documented, reproducible, and quality-controlled statistical code.
  • Experience implementing reproducible research practices and statistical programming standards.
  • Knowledge of healthcare coding systems and terminologies, including ICD-9/ICD-10, CPT/HCPCS, LOINC, RxNorm, and/or SNOMED CT.
  • Familiarity with clinical data warehouse environments and common healthcare data models.

Communication and Leadership Skills
  • Exceptional written and verbal communication skills, including the ability to communicate complex statistical concepts and findings to technical and non-technical audiences.
  • Demonstrated ability to prepare statistical reports, technical summaries, and presentations for investigators, stakeholders, sponsors, and funding agencies.
  • Strong scientific writing skills with a track record of contributing to peer-reviewed publications, grant applications, and research reports.
  • Ability to independently manage multiple projects, prioritize competing deadlines, and provide strategic statistical leadership.
  • Proven ability to work collaboratively in multidisciplinary research environments while maintaining professionalism, confidentiality, and scientific rigor.

Responsibilities
  • Serve as the lead biostatistician on assigned projects and provide statistical leadership throughout the research lifecycle.
  • Provide subject matter expertise and methodological consultation to other biostatisticians, analysts, investigators, and research staff.
  • Lead statistical and methodological design considerations for grant applications.
  • Prepare statistical reports, analytic summaries, and research deliverables for investigators, sponsors, and stakeholders.
  • Collaborate on the writing, reviewing, and editing of manuscripts for publication in peer-reviewed journals, as well as the preparation of grants.
  • Develop advanced statistical programming solutions, including SAS macros, R functions, and reproducible analytic workflows.

Minimum Education and/or Work Experience
Required Education: Master's degree and a minimum of 15 years of experience.
  • Preferred Education: PhD and a minimum of 5 years of experience.
  • Field of study: Biostatistics, Statistics, Epidemiology, Data Science, Public Health, Health Informatics, or a related quantitative field.

Required Experience:
• 3-5 years of experience as a collaborating statistician
Preferred:
• 6-10 years of experience as a collaborating statistician
• Past experience obtaining external funding as Co-I or study biostatistician
Qualifications
  • Master's degree in Biostatistics, Statistics, Epidemiology, Data Science, Public Health, Health Informatics, or a related quantitative field required; Ph.D. preferred. Candidates with a Master's degree should have a minimum of 15 years of clinical or health-related research experience. Candidates with a Ph.D. should have a minimum of 5 years of clinical or health-related research experience.
  • The ideal candidate will possess exceptional analytical, leadership, and communication skills, with demonstrated expertise in biostatistical methods, clinical and public health research, and electronic health record (EHR)-based research. The successful candidate will have experience leading statistical aspects of research projects, collaborating with multidisciplinary teams, and contributing to externally funded research initiatives.

Certificates/Credentials/Licenses
Master's degree and a minimum of 15 years of experience. PhD (preferred) and a minimum of 5 years of experience. Field of study: Biostatistics, Statistics, Epidemiology, Data Science, Public Health, Health Informatics, or a related quantitative field.
Computer Skills
Advanced proficiency in SAS and R, including development of custom SAS macros, R functions, and automated analytical workflows.
Proficiency with Microsoft Office Suite, including Word, Excel, PowerPoint, and Outlook.
Supervisory Responsibilities
No
Required operation of university owned vehicles
No
Does this position require direct animal or patient contact?
No
Physical Demands
None
Working Conditions
None
Open Date
06/10/2026
Close Date
Position Maximum Salary or Hourly Rate
$100,000/ann
Position Minimum Salary or Hourly Rate
$90,000/ann
Special Instructions to Applicants
As a Jesuit, Catholic institution of higher education, we seek candidates who will contribute to our strategic plan to deliver a Transformative Education in the Jesuit tradition. To learn more about Loyola University Chicago's mission, candidates should consult our website at www.luc.edu/mission/. For information about the university's focus on transformative education, they should consult our website at www.luc.edu/transformativeed.
About Loyola University Chicago
Founded in 1870, Loyola University Chicago is one of the nation's largest Jesuit, Catholic universities, recognized for its academic excellence, commitment to community engagement, and leadership in sustainability. A Carnegie R1 research institution, Loyola leverages its status as one of an elite group of universities with the highest level of research activity to advance knowledge that serves communities and creates global impact. With 15 schools, colleges, and institutes-including Business, Law, Medicine, Nursing, and Health Sciences-Loyola operates three primary campuses in the greater Chicago area and one in Rome, Italy, that provide students a transformative, globally connected learning experience. Consistently ranked among the nation's top universities by U.S. News & World Report, Loyola is a STARS Gold-rated institution that is ranked as one of the country's most sustainable campuses by The Princeton Review and has earned distinctions from AmeriCorps and the Carnegie Foundation for its longstanding record of service and community engagement. Guided by its Jesuit mission and commitment to caring for the whole person, Loyola educates ethical leaders who think critically, act with purpose, and strive to create a more just and sustainable world.
Loyola University Chicago strives to be an employer of choice by offering its staff and faculty a wide array of affordable, comprehensive, and competitive benefits. To view our benefits in detail, click here.
Loyola adheres to all applicable federal, state, and/or local civil rights laws and regulations prohibiting discrimination in private institutions of higher education. Please see the University's Nondiscrimination Policy.
Quick Link for Posting
https://www.careers.luc.edu/postings/35277