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Mid Level Bayesian Statistics information
What is the difference between Mid Level Bayesian Statistics vs Data Scientist?
| Aspect | Mid Level Bayesian Statistics | Data Scientist |
|---|---|---|
| Required Credentials | Master's or PhD in Statistics, Mathematics, or related field | Bachelor's or higher in Data Science, Computer Science, or related field |
| Work Environment | Research-focused, analytical, often in finance, healthcare, or academia | Cross-functional teams, data analysis, machine learning, business insights |
| Industry Usage | Statistical modeling, probabilistic analysis, research projects | Data analysis, predictive modeling, data visualization |
Mid Level Bayesian Statistics specialists focus on advanced probabilistic modeling and statistical inference, often in research or specialized industries. Data Scientists have a broader scope, combining statistical analysis with programming and machine learning to solve business problems. While both roles require strong analytical skills, Bayesian statisticians typically emphasize probabilistic models, whereas Data Scientists integrate multiple techniques for data-driven decision-making.
Other
Re-posted 26 days ago
Job description
Full Time Position:Â Biostatistics Consultant in support of the Office of Product Evaluation (OPEQ), Center for Devices and Radiological Health (CDRH), Food and Drug Administration (FDA)
Duty Description:Â The contractor shall provide expert consultant service in biostatistics consistent with (but not limited to) the following consensus standards:
- FDA "Guidance for Industry and Food and Drug Administration Staff" documents and webinars, applicable to statistical data analysis, such as Statistical Guidance on Reporting Results from Studies Evaluating Diagnostic Tests - Guidance for Industry and FDA Staff LINK, Guidance for the Use of Bayesian Statistics in Medical Device Clinical Trials LINK, and Use of Real-World Evidence to Support Regulatory Decision-Making for Medical Devices LINK.
- Applicable academic and professional consensus standards relevant to methodologies of data analysis used for clinical trials, biostatistics, real-world evidence, etc. and as applicable to the regulatory domain.
Scope of Work:Â Duties shall be provided under the direction of federal personnel, and include but are not limited to:
Provide scientific, technical, and regulatory support involving the discipline of statistics in support of assessment of regulatory submittals, and in response to questions related to the access and use of clinical evidence. This will entail application of targeted technical and/or functional expertise in one or more key areas relevant to the subject domain. Â Work will be accomplished in collaboration with more senior federal team members in achieving designated objectives.
The candidate will complete research and perform relevant analyses involving assessment of statistical aspects of regulatory submissions. These analyses should align with requirements established in applicable statutory and agency-specific guidelines, e.g., Investigation Device Exemption (IDE) under 21 CFR 812, Protection of Human Subjects under 21 CFR 50, and Institutional Review Boards under 21 CFR 5. Because FDA does not prescribe specific statistical approaches, under the guidance of more senior federal team members, the candidate will research, based on statistical practice and applicable standards, whether those included are fit for purpose and documented adequately. In conjunction with more senior federal team members, the candidate's research/analyses will contribute to decision-making (carried out at the team-level) regarding the status of regulatory submissions.Â
Specific analyses are expected to involve the following, as part of statistical analyses of Investigational Device Exemptions and assessment of clinical trial data:
- Analysis of data provided to establish safety and effectiveness of the proposed device, to include evaluation of statistical analyses used to demonstrate benefit of device use, and/or reliability.
- Assessment of pre-clinical data to determine the validity of said data, as part of determining safety and effectiveness of devices
- Analysis addressing adequacy of experimental approaches to clinical trial design and execution, e.g., trial design and protocol development, data monitoring and conduct, data management, data analysis, interpretation of results.
In general, the candidate will participate in on-site and remote meetings to discuss regulatory submissions. The work will entail a combination of collaborative, team tasks and independent research.
Minimum Candidate Requirements:
- Advanced degree in life sciences, or other area relevant to Statistics or computer science or data science
- At least 10 years of experience in relevant positions
- Advanced expertise in regulatory and/or biomedical domain may suffice in lieu of years of experience
- Experience in the conduct of statistical evaluation within the field of life science
- Programming skills in SAS and R
- Ability to work collaboratively with others in a team environment
- Strong communication skills
- Must be a United States Citizen or a Full Green Card holder