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Bayesian Modeling Jobs in Mesa, AZ (NOW HIRING)

Master Electronics

Data Scientist II

Phoenix, AZ · On-site

Design, build, and refine pricing and optimization models, including dynamic pricing, price ... Solid grounding in statistics: hypothesis testing, confidence intervals, regression, and Bayesian ...

Varsity Tutors

Statistics Graduate Level Tutor

Tempe, AZ · Remote

$18 - $40/hr

... Bayesian inference, regression analysis, multivariate methods, experimental design, and ... Ability to explain asymptotic theory, Neyman-Pearson lemma, and generalized linear models while ...

Varsity Tutors

Statistics Graduate Level Tutor

Mesa, AZ · Remote

$18 - $40/hr

... Bayesian inference, regression analysis, multivariate methods, experimental design, and ... Ability to explain asymptotic theory, Neyman-Pearson lemma, and generalized linear models while ...

Master Electronics

Data Scientist II

Phoenix, AZ

Design, build, and refine pricing and optimization models, including dynamic pricing, price ... Solid grounding in statistics: hypothesis testing, confidence intervals, regression, and Bayesian ...

Master Electronics

Data Scientist II

Phoenix, AZ

Design, build, and refine pricing and optimization models, including dynamic pricing, price ... Solid grounding in statistics: hypothesis testing, confidence intervals, regression, and Bayesian ...

All JobsBayesian Modeling JobsBayesian Modeling Jobs in Mesa, AZ

Bayesian Modeling information

See Mesa, AZ salary details

$10

$58

$82

How much do bayesian modeling jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for bayesian modeling in Mesa, AZ is $58.25, according to ZipRecruiter salary data. Most workers in this role earn between $52.21 and $67.74 per hour, depending on experience, location, and employer.

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 Mesa, AZ?

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

What job categories do people searching Bayesian Modeling jobs in Mesa, AZ look for?

The top searched job categories for Bayesian Modeling jobs in Mesa, AZ are:

Bayesian Modeling jobs near you

Data Scientist II

Master Electronics

Phoenix, AZ • On-site

Full-time

Medical, Life, Retirement, PTO

Re-posted 14 days ago

Job description

To be a family that uses our collective superpowers to do significant good.
Master Electronics has an exciting career opportunity for a Data Scientist.
As a Data Scientist, you'll be a key contributor in designing, building, and evaluating data-driven decision systems, with a strong emphasis on pricing optimization, experimentation (A/B testing), and causal analysis that directly influence product and business outcomes.
What you will do?
  • Design, build, and refine pricing and optimization models, including dynamic pricing, price elasticity estimation, margin optimization, and demand forecasting, that directly drive revenue and profitability decisions
  • Own the experimentation lifecycle: design and run A/B and multivariate tests, define success metrics and guardrails, determine sample sizes and test duration, analyze results with statistical rigor, and communicate causal impact to stakeholders
  • Apply causal inference techniques (uplift modeling, difference-in-differences, synthetic controls, instrumental variables) where randomized experiments aren't feasible
  • Translate business problems into ML solutions; build models for prediction, classification, or recommendation; implement feature engineering, model training, hyperparameter tuning, evaluation, and deployment
  • Develop scalable data pipelines on Databricks; integrate experimentation and ML systems with modern data and MLOps platforms (Databricks, MLflow); establish CI/CD pipelines, version control, testing, and monitoring to ensure model quality and reliability
  • Partner with software engineers, data engineers, product managers, and subject-matter experts; present insights and recommendations to technical and non-technical stakeholders; translate complex analyses into clear narratives
  • Research and apply emerging ML techniques; contribute to improving team standards and mentoring junior team members

What you bring to the table!
  • 3-5 years of professional experience as a data scientist or ML engineer, with a proven record of building and deploying ML models in production
  • Hands-on experience with pricing, revenue, or marketing optimization, such as price elasticity modeling, dynamic pricing, promotion optimization, or mathematical optimization methods
  • Demonstrated expertise in A/B testing and experimentation: hypothesis design, power analysis, sequential testing, guardrail metrics, and interpreting results under real-world constraints (novelty effects, interference, heterogeneous treatment effects)
    Hands-on Databricks experience for building and deploying data science workloads at scale
  • Master's degree in Computer Science, Statistics, Mathematics, Engineering, Operations Research, or a related quantitative fi eld, or a Bachelor's degree with 5+ years of equivalent professional experience
  • Strong programming skills in Python (plus experience in JavaScript), with proficiency in ML libraries (scikit-learn, PyTorch), data manipulation (pandas, SQL), and statistical analysis
  • Solid grounding in statistics: hypothesis testing, confidence intervals, regression, and Bayesian methods
  • Knowledge of MLOps tools and cloud platforms, especially Databricks (Spark, MLfl ow), AWS (S3,Redshift, SageMaker), or similar services
  • Excellent communication skills; ability to explain complex technical concepts to both technical and business audiences and to collaborate effectively across teams
  • Demonstrated ability to work independently on complex problems, manage multiple projects simultaneously, and deliver results in a fast-paced environment
    Preferred Qualifications
  • Advanced degree (Master's or PhD) in a relevant field (Statistics, Machine Learning, AI, Operations Research, Economics/Econometrics, etc.)
  • Experience with B2B or ecommerce pricing, such as quote optimization, contract pricing, or price-list management in a distribution or catalog business
  • Familiarity with experimentation platforms (in-house or commercial, e.g., Optimizely, Statsig, GrowthBook)and metric frameworks
  • Exposure to industry-specific domains such as ecommerce, marketing analytics, risk/fraud, supply chain, or logistics
  • Fluency with big data frameworks (Spark, Hadoop), streaming systems, and container/orchestration tools(Docker, Kubernetes)
  • Databricks certifications (e.g., Machine Learning Associate/Professional)
  • Knowledge of model explainability, interpretability techniques, and responsible AI

Why do you want to work with us?
Stay Healthy: World-class and affordable insurance plans ensure you and your family stay healthy
Secure Your Future: 401(k) match programwhere you are vested from day-one
Invest in Your Education: Tuition assistanceempowers you to further your education and career
Employee Assistance Program (EAP) and other incentives: Access to Perspectives, Healthcare Advocate, Working Advantage Discount Program, and more
Enjoy Work-Life-Harmony: Paid holidays, PTO accrual, Floating Holiday, and supportive personal and parental leave policies
Do Significant Good: Company-sponsored donation match 3 for 1, Volunteer Time Off (VTO) to give back to the community, and Employee Resource Groups
Provide Additional Financial Security: Company-funded and voluntary AD&D Life Insurance for you and your loved ones
If you want to learn more about our comprehensive benefits, visit: https://careers.masterelectronics.com/benefits-wellness
Equal Opportunity Employer
At Master Electronics, we thrive in a fast-paced, entrepreneurial environment where flexibility, professionalism, and a self-starter mindset aren't just preferred-they're essential. Headquartered in sunny Phoenix, AZ, we're a leading global authorized distributor of electronic components, and have been proudly family-owned for over 50 years.
What's our secret? It's simple: strong relationships, responsive service, and genuine added value. These principles have fueled our growth, allowing us to serve hundreds of thousands of customers in close partnership with world-class suppliers across the globe.
We're also deeply committed to building a workplace where everyone feels respected, supported, and empowered to succeed. Master Electronics is committed to providing equal employment opportunities for all applicants and employees. We do not unlawfully discriminate based on race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, age, disability, veteran status, marital status, creed, or any other protected characteristic.
We provide reasonable accommodations in compliance with the ADA and other applicable laws, and we strictly prohibit harassment of any kind.
This commitment applies to every part of our workplace-from recruitment and hiring to promotions, training, compensation, benefits, and even company events.

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