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Bayesian Modeling Jobs in Florida (NOW HIRING)

Opendoor

Applied Scientist- Pricing

Miami, FL · On-site

$156K - $335K/yr

Experience with one or more of the following: causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization * Comfort working with messy ...

UAB

BIOSTATISTICIAN

Tampa, FL · On-site

$60K - $98K/yr

Develop and implement advanced statistical models, including Bayesian hierarchical models, regression, survival analysis, and longitudinal data analyses techniques. * Collaborate with ...

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Bayesian Modeling information

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 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.

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 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.
What are popular job titles related to Bayesian Modeling jobs in Florida? For Bayesian Modeling jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Bayesian Modeling jobs in Florida look for? The top searched job categories for Bayesian Modeling jobs in Florida are:
Bayesian Modeling jobs near you
Applied Scientist- Pricing

Applied Scientist- Pricing

Opendoor

Miami, FL • On-site

$156K - $335K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 10 days ago

Job description

About Opendoor
At Opendoor our mission is to tilt the world in favor of homeowners and those who aim to become one. Homeownership matters. It's how people build wealth, stability, and community. It's how families put down roots, how neighborhoods strengthen, how the future gets built. We're building the modern system of homeownership giving people the freedom to buy and sell on their own terms. We've built an end-to-end online experience that has already helped thousands of people and we're just getting started.
About the Role
We're looking for an Applied Scientist to work on some of the hardest quantitative problems at Opendoor. This role will focus primarily on structural modeling, econometrics, optimization, and decision-making under uncertainty, with applications spanning pricing, resale strategy, demand modeling, and risk management.
This role will contribute to our broader valuation and pricing ecosystem and we're looking for someone who can combine strong modeling intuition with hands-on execution and strong engineering to build practical solutions for a low-margin, high-stakes business where small improvements can have an outsized impact.
You'll work on problems like modeling post-listing demand, estimating price elasticity, designing experiments, building structural models, and developing optimizers that help us make better decisions across our products and inventory.
We're a small, nimble team, so there's ample opportunity to shape both the modeling direction and how these systems get used in production decision-making.
What You'll Need
  • Experience developing quantitative models to support real-world decision-making under uncertainty
  • Strong coding skills in Python, with the ability to move beyond prototyping and implement production-quality scientific code
  • Experience with one or more of the following: causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization
  • Comfort working with messy, high-dimensional real-world data and translating ambiguous business problems into rigorous modeling approaches
  • Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, operations research, computer science, or another quantitative discipline
  • Strong communication and collaboration skills - you're comfortable working with cross-functional stakeholders and can communicate technical ideas clearly

Nice to Have
  • Experience in pricing, marketplace modeling, revenue management, supply/demand systems, inventory optimization, or risk modeling
  • Background in real estate, housing, finance, or adjacent marketplace domains
  • Familiarity with distributed data processing tools such as Pyspark
  • Experience with machine learning methods broadly, including where deep learning can complement structured statistical modeling
  • Experience working with large language models (LLMs) or vision-language models (VLMs)

What You'll Do
  • Build models that help Opendoor make better decisions around pricing, resale strategy, and portfolio risk
  • Develop demand and conversion models using both pre-listing and post-listing signals
  • Design and improve optimization frameworks that balance objectives like margin, conversion, and risk
  • Apply statistical, econometric, and mathematical modeling techniques to problems where structure matters and pure black-box prediction is not enough
  • Design experiments and measurement approaches to quantify price elasticity, customer response, and product trade-offs
  • Partner with Engineering, Product, and Operations to turn models into systems that influence real decisions
  • Bring a pragmatic, hands-on approach: move quickly from idea to prototype to production-ready scientific component

Compensation
The base pay range for this position is $156,800-$335,000 annually, plus RSUs. Pay within this range varies by work location and may also depend on your qualifications, job-related knowledge, skills, and experience. We also offer a comprehensive package of benefits including unlimited PTO, medical/dental/vision insurance, life insurance, and 401(k) to eligible employees.
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