1

Bayesian Modeling Jobs in Arkansas (NOW HIRING)

Bayesian approaches and conformal prediction to manage the risk of price changes. * Build explainable pricing systems: Provide model interpretability and stakeholder-facing narratives on "why" a ...

Bayesian approaches and conformal prediction to manage the risk of price changes. * Build explainable pricing systems: Provide model interpretability and stakeholder-facing narratives on "why" a ...

Bayesian approaches and conformal prediction to manage the risk of price changes. * Build explainable pricing systems: Provide model interpretability and stakeholder-facing narratives on "why" a ...

Bayesian approaches and conformal prediction to manage the risk of price changes. * Build explainable pricing systems: Provide model interpretability and stakeholder-facing narratives on "why" a ...

Bayesian approaches and conformal prediction to manage the risk of price changes. * Build explainable pricing systems: Provide model interpretability and stakeholder-facing narratives on "why" a ...

Bayesian approaches and conformal prediction to manage the risk of price changes. * Build explainable pricing systems: Provide model interpretability and stakeholder-facing narratives on "why" a ...

Bayesian approaches and conformal prediction to manage the risk of price changes. * Build explainable pricing systems: Provide model interpretability and stakeholder-facing narratives on "why" a ...

Bayesian approaches and conformal prediction to manage the risk of price changes. * Build explainable pricing systems: Provide model interpretability and stakeholder-facing narratives on "why" a ...

Bayesian approaches and conformal prediction to manage the risk of price changes. * Build explainable pricing systems: Provide model interpretability and stakeholder-facing narratives on "why" a ...

Bayesian approaches and conformal prediction to manage the risk of price changes. * Build explainable pricing systems: Provide model interpretability and stakeholder-facing narratives on "why" a ...

(USA) Data Scientist III

Greenland, AR · On-site

$90K - $180K/yr

Advanced proficiency in statistical methods, machine learning algorithms, and analytical modeling techniques including Bayesian inference and neural networks. * Strong programming skills in SQL ...

(USA) Data Scientist III

Lowell, AR · On-site

$90K - $180K/yr

Advanced proficiency in statistical methods, machine learning algorithms, and analytical modeling techniques including Bayesian inference and neural networks. * Strong programming skills in SQL ...

next page

Showing results 1-20

Bayesian Modeling information

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.

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 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.

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 popular job titles related to Bayesian Modeling jobs in Arkansas?

For Bayesian Modeling jobs in Arkansas, the most frequently searched job titles are:

What cities in Arkansas are hiring for Bayesian Modeling jobs?

Cities in Arkansas with the most Bayesian Modeling job openings:

Contractor

Re-posted 6 days ago


Job description

1. Job Title : Looking for Data Scientist 2. Job Summary : skill set: Data Science Experience in deep learning Machine leraning Future engineering Proficiency in R Programming Proficiency in Relational Programming such as SQL Spark and Hive proficiency in NLP and unstructured data analysis proficiency in data simulation bootstrapping techniques Experience with Customer Analytics Proficiency in multiple supervised ML models including GBM Random Forests and supervised clustering Specialty in Bayesian Statistics Bootstrapping and Data Simulation Experience in Big Data Environments such as Hadoop Spark and Hive Natural language processing 3. Shift : 10 to 8 PM EST 4. Roles & Responsibilities :Data Scientist 5. Demand requires Travel? : no 6. Certification(s) Required : no
Hours : 8:00am to 5:00pm
Education :
Additional Job Details : Must Have Skills Data Science Assortment Management Good To Have Skills 3NF data modeling PL/SQL Qualifications - External