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Bayesian Networks Jobs (NOW HIRING)

Data Scientist

San Ramon, CA · On-site

$93 - $98/hr

Experience with forecasting, Bayesian networks, and graph analytics. * Knowledge of program management theories, concepts, methods, best practices, and techniques. Skills: * Strong statistics ...

Extensive knowledge of various data modeling techniques, including advanced methods such as deep learning, Bayesian networks, and causal inference, and the ability to apply them to solve complex ...

Postdoctoral Fellow I

Logan, UT

$42K - $57K/yr

Knowledge about PINs, graphical models such as the dynamic Bayesian networks. Along with the online application, please attach: 1. Resume/CV to be uploaded at the beginning of your application in the ...

Postdoctoral Fellow I

Logan, UT · On-site

$42K - $57K/yr

Knowledge about PINs, graphical models such as the dynamic Bayesian networks. Required Documents Along with the online application, please attach: 1. Resume/CV to be uploaded at the beginning of your ...

Data Scientist

Ashburn, VA · On-site

$83K - $139K/yr

... Bayesian Networks, etc. * Experience with pattern recognition and extraction, automated classification, and categorization and with entity resolution (e.g., record linking, named entity matching ...

EPSS, Attack trees/graph quantification, Monte Carlo simulations, Bayesian networks) * Prior experience with the risk analysis of complex embedded systems and a demonstrated skill in turning the ...

Data Scientist

Ashburn, VA · Hybrid

$83K - $139K/yr

... Bayesian Networks, etc. * Experience with pattern recognition and extraction, automated classification, and categorization and with entity resolution (e.g., record linking, named entity matching ...

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Bayesian Networks information

What are Bayesian networks?

Bayesian Networks are probabilistic graphical models that represent a set of variables and their conditional dependencies using a directed acyclic graph. They are used to model uncertainty in complex systems by encoding relationships between variables and allowing for efficient inference and reasoning. These networks are widely applied in fields such as machine learning, diagnostics, decision support, and bioinformatics to help predict outcomes and understand causal relationships.

What are some common challenges faced by professionals working with Bayesian networks in real-world projects?

Professionals working with Bayesian Networks often encounter challenges such as handling incomplete or noisy data, defining accurate conditional dependencies, and ensuring computational efficiency for large or complex networks. Collaboration with domain experts is crucial to correctly structure the network and validate assumptions. Additionally, integrating Bayesian models with existing data systems and effectively communicating probabilistic results to non-technical stakeholders are important aspects of the role.

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

To thrive as a Bayesian Networks Specialist, you need a strong background in statistics, probability theory, and machine learning, often supported by a degree in computer science, mathematics, or a related field. Proficiency with programming languages such as Python or R, and experience using specialized libraries like pgmpy or bnlearn, are typically required. Strong analytical thinking, problem-solving ability, and effective communication skills set standout professionals apart in this role. These competencies are crucial for designing, implementing, and interpreting Bayesian models that inform critical decision-making in complex domains.

What is the difference between Bayesian Networks vs Data Analysts?

AspectBayesian NetworksData Analysts
Required CredentialsStatistics, Data Science, Computer Science degrees; certifications in probabilistic modelingStatistics, Data Science, Business Analytics degrees; certifications in data analysis tools
Work EnvironmentResearch, modeling, and algorithm development in tech or research firmsData interpretation, reporting, and visualization across various industries
Industry UsageUsed for probabilistic reasoning, decision support, and machine learningUsed for data interpretation, reporting, and business insights

Bayesian Networks focus on probabilistic modeling and decision-making algorithms, often requiring advanced statistical knowledge. Data Analysts primarily interpret and visualize data to inform business decisions. While both roles involve data, Bayesian Networks are more technical and model-driven, whereas Data Analysts focus on data interpretation and reporting.

More about Bayesian Networks jobs

What cities are hiring for Bayesian Networks jobs?

Cities with the most Bayesian Networks job openings:

What states have the most Bayesian Networks jobs?

States with the most job openings for Bayesian Networks jobs include:

Infographic showing various Bayesian Networks job openings in the United States as of August 2026, with employment types broken down into 33% Full Time, 66% Part Time, and 1% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution.

Senior Data Scientist - ML, Python

San Antonio, TX • On-site

Abode TechZone, LLC
Recruiting and Staffing Services • 11 - 50 employees

Full-time

Re-posted 18 days ago


Job description

Job Summary:
Abode TechZone, LLC is seeking a Senior Data Scientist with expertise in machine learning and statistical modeling. The role involves coding and testing analytical models, implementing best practices, and utilizing various data science techniques to provide analytical solutions for the business.
Responsibilities:
• Responsible for coding and testing customized analytical models of medium to high degree of complexity.
• Must be able to implement best practices when writing and testing code.
• Familiarity with the life cycle of a data science project and extensive experience with python and XGboost, Arima/Sarima is a must.
• Requires strong interpersonal and communication skills, operational Elasticsearch knowledge and ability to construct GUI interfaces.
• Gathers, interprets, and manipulates structured and unstructured data to enable analytical solutions for the business.
• Selects the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs.
• Proven experience in developing models using Regression, Decision trees, Bayesian networks, Random Forest, Logistic regression, Support vector machine, Gradient boosting algorithms, Clustering algorithms and Dimensionality Reduction Algorithms.
• Proven experience in building and implementing Timeseries and forecasting models.
• Experience in Deep Learning model development using TensorFlow, Keras, PyTorch.
• Hands on experience in building ML workflows.
• Experience in Model implementation, Governance, and monitoring.
• Responsibilities include Performing the code development of complex analytic algorithms and paradigms, perform a clear breakdown of the analytic functionality and separate it into working modules.
• Working experience in Python, R and SQL.
• Experience in Python data science packages such as numPy, SciPy and SciKit-learn.
Qualifications:
Required:
• Strong expertise in data science, machine learning, and statistical modeling.
• Proficiency in tools and languages such as Python, SQL, pySpark, ML packages.
• Expertise in building – XGBoost type classification models and ARIMA/SARIMA type forecasting models.
• Bachelor's or Master's degree in Mathematics, Physics, Data Science, Statistics, AI/ML.
• Good experience in quantitative analytics or data science.
• Familiarity with the life cycle of a data science project and extensive experience with python and XGboost, Arima/Sarima is a must.
• Requires strong interpersonal and communication skills, operational Elasticsearch knowledge and ability to construct GUI interfaces.
• Gathers, interprets, and manipulates structured and unstructured data to enable analytical solutions for the business.
• Selects the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs.
• Proven experience in developing models using Regression, Decision trees, Bayesian networks, Random Forest, Logistic regression, Support vector machine, Gradient boosting algorithms, Clustering algorithms and Dimensionality Reduction Algorithms.
• Proven experience in building and implementing Timeseries and forecasting models.
• Experience in Deep Learning model development using TensorFlow, Keras, PyTorch.
• Hands on experience in building ML workflows.
• Experience in Model implementation, Governance, and monitoring.
• Responsibilities include Performing the code development of complex analytic algorithms and paradigms, perform a clear breakdown of the analytic functionality and separate it into working modules.
• Working experience in Python, R and SQL.
• Experience in Python data science packages such as numPy, SciPy and SciKit-learn.
Preferred:
• Fluent with Natural Language Processing and text analytics libraries (NLTK, SpaCy).
• Experience with Data Science Platforms (Dataiku, H2o, Azure...).
• Experience with one of Subversion/SVN, Git, GitHub, GitLab, Mercurial, or other version control system.
• Experience with cloud platforms AWS, Azure, GCP a plus.
• Knowledge in Big Data, Hadoop, HIVE/HQL, HDFS, Spark/PySpark, Kafka.
• Familiar working in an AGILE environment.
Company:
Abode TechZone LLC is fast growing staffing corporation, business growth depends on putting the right people in place — the professional talent that sets your organization apart from the competition. Founded in 2019, the company is headquartered in New York, USA, with a team of 11-50 employees. The company is currently Early Stage.

Abode TechZone logo

About Abode TechZone

Sourced by ZipRecruiter

Abode is fast-growing staffing corporation, business growth depends on putting the right people in place — the professional talent that sets your organization apart from the competition. Abode’s vision is to provide best ever IT’s Staff Solutions services with an effective strategy which can address market fluctuations in key areas, such as time, cost, risk, flexibility, control, and expertise. We target to connect our partners with the best professional talent you need.

Industry

Recruiting and staffing services

Company size

11 - 50 Employees

Headquarters location

New York, NY, US

Year founded

2019

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