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Postdoctoral In Bayesian Statistics Jobs in Loretto, MN

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Postdoctoral In Bayesian Statistics information

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$25.8K

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$86.2K

How much do postdoctoral in bayesian statistics jobs pay per year?

As of Sep 14, 2026, the average yearly pay for postdoctoral in bayesian statistics in Loretto, MN is $60,953.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,600.00 and $68,700.00 per year, depending on experience, location, and employer.

What is a postdoctoral position in Bayesian statistics?

A Postdoctoral position in Bayesian Statistics is a research-focused role for individuals who have recently completed their PhD in statistics, mathematics, or a related field. These positions involve conducting advanced research using Bayesian methods, which apply probability to infer statistical conclusions. Postdocs often work on developing new Bayesian models, collaborating on interdisciplinary projects, and publishing research findings. Such positions are typically temporary and designed to further prepare researchers for academic, industry, or governmental roles.

What are the key skills and qualifications needed to thrive as a postdoctoral researcher in Bayesian statistics?

To thrive as a Postdoctoral Researcher in Bayesian Statistics, you need an advanced degree (typically a PhD) in statistics or a related field, with strong expertise in Bayesian inference and probabilistic modeling. Proficiency with statistical programming languages such as R, Python, or Stan, and experience with specialized Bayesian analysis software are highly valued. Excellent problem-solving skills, collaboration, and the ability to communicate complex statistical concepts clearly are standout soft skills for this role. These skills and qualities are crucial for conducting rigorous research, publishing impactful results, and contributing effectively to scientific teams.

What are some common challenges faced by postdoctoral researchers in Bayesian statistics, and how can they be addressed?

Postdoctoral researchers in Bayesian statistics often encounter challenges such as managing complex, high-dimensional data, staying current with rapidly evolving computational methods, and balancing independent research with collaborative projects. Effective strategies include leveraging open-source statistical software, actively participating in seminars and workshops to stay updated, and establishing regular communication with interdisciplinary teams. Building a strong professional network and seeking mentorship within the department can also help in navigating research obstacles and advancing one's career.

What is the difference between Postdoctoral In Bayesian Statistics vs Postdoctoral In Data Science?

AspectPostdoctoral In Bayesian StatisticsPostdoctoral In Data Science
Required CredentialsPhD in Statistics, Mathematics, or related fieldPhD in Computer Science, Statistics, or related field
Work EnvironmentAcademic research, university labsResearch institutions, tech companies, industry labs
Employer & Industry UsageUniversities, research institutesTech firms, finance, healthcare, consulting
Common Search & Comparison IntentSpecialized research roles in Bayesian methodsBroader data analysis and machine learning roles

Postdoctoral In Bayesian Statistics focuses on advanced research in Bayesian methods within academic settings, requiring deep statistical expertise. In contrast, Postdoctoral In Data Science covers a broader range of data analysis techniques, including machine learning, often in industry environments. Both roles require a PhD but differ in application focus and work environment.

Infographic showing various Postdoctoral In Bayesian Statistics job openings in Loretto, MN as of September 2026, with employment types broken down into 2% Internship, 79% Full Time, 18% Part Time, and 1% Contract. Highlights an 80% Physical, 4% Hybrid, and 16% Remote job distribution, with an average salary of $60,953 per year, or $29.3 per hour.

Principal Data Scientist - Remote

Minnetonka, MN • On-site, Remote

UnitedHealth Group
Insurance Services • 10K+ employees

Full-time

Retirement

Re-posted 6 days ago


UnitedHealth Group rating

7.6

Company rating: 7.6 out of 10

Based on 146 frontline employees who took The Breakroom Quiz


Job description

At UnitedHealthcare, we're simplifying the health care experience, creating healthier communities and removing barriers to quality care. The work you do here impacts the lives of millions of people for the better. Come build the health care system of tomorrow, making it more responsive, affordable and optimized. Ready to make a difference? Join us to start Caring. Connecting. Growing together

 

As a Principal Data Scientist within the Optum Technology team supporting UHC Technology, you will lead the design, development, and deployment of advanced machine learning and generative AI solutions. In this role, you will define end-to-end ML architecture, select appropriate tools and frameworks, drive proof-of-concept experiments, and guide engineering teams in productionizing scalable AI services. You will balance architectural leadership with hands-on execution across complex initiatives, establishing best practices for model governance, reproducibility, and security to drive healthcare innovation.

You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.  

 

Primary Responsibilities: 

  • Design, develop, and deploy scalable, production-grade AI solutions to address complex business challenges while embedding responsible AI principles, fairness, transparency, and accountability throughout the model development lifecycle
  • Lead solution architecture and hands-on development across complex AI/ML initiatives using traditional ML, deep learning, and modern LLM-based approaches
  • Lead proof-of-concept experiments in generative AI (transformers, GANs, diffusion models) and evaluate emerging tools, research, and frameworks to drive strategic innovation
  • Collaborate with research, data engineering, software engineering, and product teams to translate cutting-edge AI advancements into scalable, production-ready capabilities
  • Define and establish enterprise best practices for model governance, versioning, reproducibility, security, and cloud-native MLOps pipelines
  • Provide technical guidance, architectural design reviews, and mentorship to junior engineers and data scientists without formal people management duties
  • Document architecture designs, technical proposals, and recommendations, presenting findings directly to cross-functional stakeholders and leadership
     

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Required Qualifications: 

  • 10+ years of experience designing, building, and deploying production machine learning solutions
  • 3+ years of experience building Generative AI applications using LLMs and orchestration frameworks such as LangChain and/or LangGraph
  • Deep expertise in either NLP or Computer Vision with multiple years of hands-on solution ownership in that domain
  • Proven solid foundation in core ML and statistical methods (supervised/unsupervised learning, regression, classification, clustering, time series, Bayesian modeling) alongside substantive deep learning experience
  • Demonstrated experience with cloud ML services and infrastructure design on at least one major cloud platform (AWS, Azure, or GCP), including containerization (Docker/Kubernetes) and MLOps (CI/CD, model registry, monitoring)
  • Proven track record of successfully moving models from research/POC phase into production at scale
  • Hands-on programming proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow)
  • Demonstrated solid background in probability, linear algebra, and statistical inferenc
  • Demonstrated problem-solving ability with clear verbal and written communication skills

 

Preferred Qualifications:  

  • Experience working with healthcare data, clinical systems, or U.S.-based healthcare environments
  • Practical experience fine-tuning generative models (e.g., GPT, BERT, Stable Diffusion, or custom architectures)
  • Experience with MLOps tools such as MLflow, Kubeflow, TFX, or Airflow
  • Familiarity with big data technologies including Apache Spark, Hadoop, or Dask
  • Knowledge of data visualization tools (Tableau, Power BI) and dashboard design

*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy  

Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $112,700 to $193,200 annually based on full-time employment. We comply with all minimum wage laws as applicable.

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.    

 

 

UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.      

 

UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment.  


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