1

Bayesian Modeling Jobs in Watertown, MA (NOW HIRING)

... outsourced model * partnering closely with the cross-functional teams and providing expert ... Advanced knowledge of statistical methods in clinical study designs (adaptive, Bayesian ...

Lead inverse design and model-based discovery efforts using Bayesian optimization, diffusion models, or related methods. * Collaborate with scientists to integrate domain knowledge into deep learning ...

Senior Data Scientist

Boston, MA · On-site +1

$140K - $190K/yr

Create and refine predictive models (Bayesian inference, regression analysis, time-series forecasting) to address other key clinical trial challenges and improve decision-making. * AI Monitoring and ...

Lead inverse design and model-based discovery efforts using Bayesian optimization, diffusion models, or related methods. * Collaborate with scientists to integrate domain knowledge into deep learning ...

Broad knowledge of statistical modeling is required, including all standard methods in Bayesian hierarchical modeling and computing, methods for longitudinal and time-to-event data, propensity ...

Broad knowledge of statistical modeling is required, including all standard methods in Bayesian hierarchical modeling and computing, methods for longitudinal and time-to-event data, propensity ...

Experience with Spark, Kaplan, Breeze, map/reduce models a plus Experience modeling stochastic processes, Bayesian learning models, utility theory, game theory a plus Additional Information All your ...

Experience with Spark, Kaplan, Breeze, map/reduce models a plus Experience modeling stochastic processes, Bayesian learning models, utility theory, game theory a plus Additional Information All your ...

Statistician Intern

Boston, MA · On-site +1

$54K - $66K/yr

... Bayesian and frequentist (network) meta-analysis techniques. The results of each analysis can feed into publications, value materials, health economic models or health technology assessment ...

Statistician Intern

Boston, MA · On-site

$54K - $66K/yr

... Bayesian and frequentist (network) meta-analysis techniques. The results of each analysis can feed into publications, value materials, health economic models or health technology assessment ...

Showing results 21-40

Bayesian Modeling information

See Watertown, MA salary details

$11

$63

$90

How much do bayesian modeling jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for bayesian modeling in Watertown, MA is $63.86, according to ZipRecruiter salary data. Most workers in this role earn between $57.26 and $74.23 per hour, depending on experience, location, and employer.

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.

Senior Director, Biostatistics

Jobtailor

Cambridge, MA • On-site

$150 - $190/hr

Other

Re-posted 2 days ago


Job description

Responsibilities
  • acting as the statistical lead for one program or multiple programs
  • providing technical leadership and statistical support on the design, conduct and execution of the clinical studies
  • oversight of the statistics and programming team through an outsourced model
  • partnering closely with the cross-functional teams and providing expert biostatistics input on development plans, regulatory interactions, and study design
  • authoring/review of statistics section in the protocol, sample size determination, authoring/review of statistical analysis plan and mock TFL, reviewing study randomization files, ADaM specs, CRF design, DMC charter
  • analyzing and interpreting the clinical study results, and ensuring statistical integrity
Requirements
  • PhD in statistics strongly preferred; Candidates with MS in statistics, biostatistics or mathematics and a depth of relevant experience in drug development statistical research will be considered
  • A minimum of 8 years’ experience in progressive and relevant clinical trial experience
  • Experience leading teams and working in a matrix organization
  • Experience with blinded study designs and analyzing and interpreting patient reported outcome (PRO) data sets strongly preferred
  • Ability to communicate and work directly with non-statisticians imparting and delivering complex statistical information to scientific development partners and researchers
  • Excellent communication with an ability to present to a variety of stakeholders and tailor message accordingly
  • Experience managing CROs and other data vendors
  • Strong leader with a growth mindset, willing to learn from others, and dedicated to promoting a collaborative work culture
  • Ability to keep pace in a fast-moving organization and navigate ambiguity
  • Advanced knowledge of statistical methods in clinical study designs (adaptive, Bayesian), statistical analysis methods including Bayesian method, missing data imputation, multiplicity adjustment
  • Knowledge and proficiency in SAS or R and other industry computational toolsKnowledge of CDISC standard including SDTM, ADaM
  • Knowledge of ICH guidelines, FDA / EMA / other regulatory authority guidance
  • Experience in planning, running and documenting simulations, including clinical trial simulations
  • Experience working on site and with remote teams
  • Ability and willingness to travel up to 10% or as needed by the business
#J-18808-Ljbffr