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Bayesian Phd Jobs in Florida (NOW HIRING)

MMS

Study Design Statistician (US)

Miami, FL · On-site

... PhD preferred. * 5-7 years of experience in the application of medical statistics (pharma, CRO ... Experience of Bayesian approaches to design and analysis of clinical data preferred. * Experience ...

Opendoor

Applied Scientist- Pricing

Miami, FL · On-site

$156K - $335K/yr

Experience with one or more of the following: causal inference, Bayesian modeling, structural ... Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, operations research ...

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Bayesian Phd information

What are some common challenges faced by a Bayesian PhD researcher during collaborative projects?

Bayesian PhD researchers often collaborate with interdisciplinary teams, which can present challenges such as communicating complex statistical concepts to non-specialists and integrating Bayesian methods with other analytical frameworks. Balancing the depth of theoretical work with practical problem-solving, managing computational demands, and aligning project goals with collaborators' expectations are also common hurdles. Successful collaboration typically requires strong communication skills, adaptability, and a willingness to bridge methodological gaps between disciplines.

What are the key skills and qualifications needed to thrive as a Bayesian PhD?

To thrive as a Bayesian PhD, you need advanced knowledge of probability theory, statistical inference, and mathematics, typically supported by a doctoral degree in statistics, mathematics, or a related field. Proficiency with statistical programming languages like R, Python, and specialized Bayesian tools such as Stan or BUGS is essential. Strong critical thinking, problem-solving, and clear communication skills help in articulating complex analyses and collaborating across disciplines. These capabilities are crucial for developing rigorous models, conducting impactful research, and translating statistical insights into actionable solutions.

What is the difference between Bayesian Phd vs Data Scientist?

AspectBayesian PhdData Scientist
Required CredentialsPhD in Statistics, Mathematics, or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentResearch-focused, academic or specialized industry rolesBusiness-focused, tech companies, or consulting firms
Industry UsageAcademic research, advanced analytics, specialized modelingData analysis, machine learning, business insights
Common Search/ComparisonYesYes

While a Bayesian PhD specializes in advanced statistical modeling and research, a Data Scientist applies data analysis and machine learning techniques in practical business contexts. Both roles require strong analytical skills, but the Bayesian PhD typically focuses on theoretical development, whereas the Data Scientist emphasizes application and implementation.

What is a Bayesian PhD?

A Bayesian PhD typically refers to an individual who has completed a doctoral program with a focus on Bayesian statistics or Bayesian methods in their research. Bayesian statistics is a branch of statistics that uses probability distributions to represent uncertainty about unknowns, updating beliefs as new data becomes available. Students in this field learn to develop and apply Bayesian models to a wide range of problems in science, engineering, and social sciences. A PhD program with a Bayesian focus often involves advanced coursework in probability theory, statistical inference, and computational methods, as well as original research using Bayesian approaches.

What are popular job titles related to Bayesian Phd jobs in Florida?

For Bayesian Phd jobs in Florida, the most frequently searched job titles are:

What job categories do people searching Bayesian Phd jobs in Florida look for?

The top searched job categories for Bayesian Phd jobs in Florida are:

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Cities in Florida with the most Bayesian Phd job openings:

Bayesian Phd jobs near you

Senior Data Scientist Contractor (1099)

WiredPeople, Inc.

Tallahassee, FL • On-site, Remote

Contractor

Posted 12 days ago

Job description

WiredPeople is looking for a senior-level Data Scientist who can operate independently to drive advanced statistical modeling, complex analytics, and research initiatives. The ideal candidate brings a unique blend of deep technical expertise, strategic consulting experience, and a proven track record of working directly with external clients, particularly government stakeholders.
In this role, you will provide analytical leadership, define technical approaches, and translate highly complex data into actionable insights for non-technical audiences. Experience working with healthcare, public health, research, or government-related data projects is highly desirable. We are currently seeking a highly skilled Senior Data Scientist Contractor (1099) to join our network and support complex analytics and research projects for our clients.
Key Responsibilities
  • Analytical Leadership: Independently define analytical approaches, design research methodologies, and provide strategic recommendations to stakeholders.
  • Advanced Statistical Modeling: Develop, validate, and productionize machine learning models, utilizing techniques such as predictive modeling, Random Forest, Bayesian hierarchical modeling, and geospatial analysis.
  • Client Consulting: Work directly with external clients and government stakeholders to understand project needs, manage expectations, and deliver high-quality data science solutions.
  • Data Translation: Effectively present complex technical findings, methodologies, and actionable insights to non-technical stakeholders and decision-makers.
  • Data Management & Pipeline Development: Oversee ETL/ELT pipeline development, ensuring robust data governance, access controls, and secure handling of sensitive health and regulated datasets.
  • Technical Execution: Utilize an advanced technology stack, including Azure Databricks, R, and SQL, to build and deploy scalable data science solutions.

Must-Have Qualifications
  • Cloud & Architecture: Intermediate to Advanced experience in Microsoft Azure, specifically Azure Databricks.
  • Programming: Advanced proficiency in R and strong SQL and database management experience.
  • Machine Learning: Proven experience with ML techniques, including predictive modeling and Random Forest.
  • Data Security & Ethics: Experience handling sensitive health, research, or highly regulated datasets. Must hold a current CITI Certification (or have the ability to quickly obtain one).
  • Development Tools: Advanced R Shiny experience and familiarity with GitHub and CI/CD pipelines (highly preferred).

Preferred Senior-Level Experience
  • Education: PhD or extensive applied Data Science experience in a related field.
  • Advanced Modeling: Deep expertise in Bayesian hierarchical modeling, spatial/geospatial modeling, model validation, and advanced statistical analysis.
  • Industry Experience: Prior consulting experience with external clients, particularly supporting government or public-sector clients.

Technical Environment Candidates with hands-on experience in the following technical areas will stand out:
  • Cloud Platform: Azure Databricks
  • Data Warehousing: Snowflake, PostgreSQL, or similar data warehouse environments
  • Data Engineering: ETL/ELT pipeline development
  • Databases: Relational and NoSQL databases
  • Data Management: Data governance and strict access controls
  • MLOps: Productionizing and deploying machine learning models

Additional Information
  • Job Type: Contract (1099)
  • Industry Focus: Healthcare, Public Health, Government Services

WiredPeople provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, WiredPeople complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

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