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Bayesian Networks Jobs in Texas (NOW HIRING)

Unlike ad networks or signage companies, Atmosphere is the only true TV company whose first ... Background in Bayesian inference or probabilistic modeling. * Experience launching data products in ...

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

Use machine learning and statistical modelling techniques such as Decision Trees, Logistic Regression, Neural Networks, Bayesian Analysis and others to develop and evaluate algorithms for improving ...

Showing results 21-25

Bayesian Networks information

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.

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 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 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 cities in Texas are hiring for Bayesian Networks jobs?

Cities in Texas with the most Bayesian Networks job openings:

Data Analyst -- Telecom

Way Forward Consulting

Plano, TX • On-site

Other

Posted 24 days ago


Job description

W2 job to a staffing company Top skills: -Data Modeling -Machine Learning -Artificial Intelligence Schedule: Fully onsite KEY RESPONSIBILITES/REQUIREMENTS: As a Performance Assurance Machine Learning Engineer, you will work under the coaching of Senior and Lead engineers of the Data Science & Tools Team to analyze Samsung’s deployed network elements. You will utilize skills to query databases to extract data, use skills in Python or R to analyze data such that you can identify 4G/5G network infrastructure and performance issues and build prediction models, ad-hoc tools, and dashboards to communicate your findings with your team and peers Specific Responsibilities include: • 7+ years of professional experience in Data Science, Data Analytics, and/or Data Engineering with abilities to work with large datasets using demonstrated statistical, predictive modeling and machine learning methods. • 3-5 years demonstrated experience on designing, deploying, and maintaining large scale ML systems in a production environment. • Work closely with the internal and external stakeholders to explore relationships of 4G/5G KPI measurements and targets (KPI, KQI) for 4G/5G RAN product acceptance and performance monitoring. • Collaborate with RF engineers, network engineers, data scientists, platform engineers, product teams, and operations stakeholders to ensure ML outputs are technically accurate, interpretable, and operationally useful. • Utilize A/B testing, statistical, and machine learning models to build robust mechanism for product & feature performance analysis, for evaluation of new product & SW releases and 3rd party product evaluation. • Aid in product & feature performance analysis, evaluation of new product & SW releases and 3rd party product evaluation using analytics/data science to drive intelligent business decisions. • Work with the team to proactively define and interpret data/metrics/KPIs, analyze results, and provide insights to determine operational impact, trends and opportunities for all the 4G/5G RAN products. • Prototyping use cases, implementing automations, and developing tools to support and augment manual or repetitive efforts. • Communicate key findings to stakeholders using visualizations and/or other suitable methods. • Excellent verbal and written communication skills to communicate technical and complex concepts in an easy-to-follow progression. • Able to compile analysis output and findings into a succinct story for technical and non-technical audiences. • Adapt to changes in a dynamic business environment and, support management initiatives. Background & Competencies Required: • Graduate Degree in Computer Science, Statistics, Data Science or a related Data Engineering with 7+ years of professional experience is preferred. • Programming experience: Python & Spark (preferred) and/or other languages such as R , SQL, Hive, Spark, Javascript, Visual Basic, C++, shell scripting in a linux or IDE environment such as VSCODE, Jupyter, RStudio, etc. • Cloud Development Experience – AWS/Azure/Google utilizing cloud providers such as Databricks or Snowflake • Machine learning expertise: GLM Regression (Linear, Logistic, Multinomial), Decision Tree (including Boosted Trees, Random Forest), kMeans/Hierarchical Clustering, Principle Component Analysis, t-SNE, Neural Networks such as transformers and auto-encoders, Bayesian Regression, and Times Series Modeling. • Experience using data with high-volume (1TB+) & high-dimensionality (500+ variables per schema), especially within a big data framework (HaDoop, Citus, MongoDB, etc). • Experience performing Data Wrangling, Exploratory Data Analysis (EDA), Correlation Analysis, Statistical Methodologies (distributions, hypothesis testing, confidence intervals) & Significance Testing, A/B Testing. • Experience with MLOPS concepts and environments such as MLFLOW a plus. • Experience with basic linux administration and software development in a linux environment. • Experience in hardware resource management and configuration – CUDA, Docker, KubeFlow, Kubernetes, etc a plus • Must possess qualities of being curious and eagerness to learn . • Experience with data visualization and ability to quickly grasp statistical methods, and methodologies. Maintain a strong command of current data analytics technology trends, including emerging paradigms and practices. • Demonstrated research and problem solving skills via prior work experience. Experience with wireless infrastructure provider and/or operator is desired. • Technical knowledge of any wireless technology & procedures including CDMA/EVDO/LTE/Volte and/or 5G a plus. • Experience with evaluating service performance trends and proactively defining RAN system performance related issues a plus. • Experience of software version control, coding best practices, and use of development management software such as github, bitbucket, etc is desired. • Must have a strong work ethic, integrity and work extremely well independently or in a team environment. Physical/Mental Demands and Working Conditions: The position requires the ability to perform the essential duties and responsibilities in the following environment: • Excellent interpersonal and communication skills. Must be skilled in developing and maintaining good working relationships with all appropriate levels within and outside the company. • Operate a computer keyboard and view a video display terminal more than 75% of work time in an office work environment • Frequently works additional hours beyond normal schedule. • Performs work under time schedules and stresses which are normally periodic or cyclical and include time sensitive job stress, fatigue, unpaid over-time, intellectual challenge, constant technical data feedback, language barriers, and project management stress. • Machines, tools, equipment, and work aids include PC’s, printers, etc. most often associated with office work area equipment.