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Bayesian Modeling Jobs in Massachusetts (NOW HIRING)

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 ...

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 ...

Sr. Director, Biostatistics

Cambridge, MA · On-site

$270K - $290K/yr

You will have oversight of the statistics and programming team through an outsourced model. You ... Advanced knowledge of statistical methods in clinical study designs (adaptive, Bayesian ...

Sr. Director, Biostatistics

Cambridge, MA · On-site

$270K - $290K/yr

You will have oversight of the statistics and programming team through an outsourced model. You ... Advanced knowledge of statistical methods in clinical study designs (adaptive, Bayesian ...

... Bayesian statistics, Time-Series analysis, and non-linear tree-based models. * DE streamlining data preparation pipeline using relational databases (Oracle and Snowflake) and performing manipulation ...

Showing results 41-60

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 cities in Massachusetts are hiring for Bayesian Modeling jobs? Cities in Massachusetts with the most Bayesian Modeling job openings:

Data Scientist Opportunity

Bridge Tech

Boston, MA

Full-time

Re-posted 18 days ago


Job description

Job Description

The Data Science team is responsible for managing all data analytics, reporting and algorithmic aspects for our client.  The data science team is an integral part of every function in the life cycle of the company to provide product, tools, business support.  As a data scientist you will work closely with architects, engineers, account managers and data scientists within and outside the company.  You will be involved from pre-sales to support. You will work on next generation algorithms development and help measure, maintain and upgrade current business.  

Qualifications

REQUIRED SKILLS
Outstanding technical abilities with 5+ years of Scala, Java, or C/C++ development experience with statistical machine learning models
Rounded business skills with the ability to understand customer business needs
Ability to solve problems practically for clients and internal needs
Excellent interpersonal skills with ability to communicate clearly and concisely with executives, engineers, account managers, sales, business partners and data scientists.
Ability to respond to customer needs and meet deadlines with accurate work while under pressure
Expected to build statistical, optimization and machine learning models followed by detailed pre-production out of sample validation and recommendation for a/b testing experiments with success criteria.
Own complete life cycle from problem formulation to solution deployment and maintenance
Excellent understanding of computer science fundamentals, data structures, and algorithms
Have a strong mathematical background and have experience with modeling complex high dimensional problems
Experience performing petabyte scale data analysis and developing meaningful visualizations
Must be able to collaborate with architects, engineers, and data scientists within and outside the company.
EXPERIENCE
Proven to thrive in start up environments
Experience defining and building web scale algorithms, reports and visualizations
Must be organized, have an eye for detail, and be able to put ideas into a tangible form
Ability to prioritize and manage work to critical project timelines in a fast-paced environment and the ability to develop new approaches to complex design problems
Experience with developing production grade algorithms for the web scale
Preferred - Ph.D. in Computer Science, Operations Research, Physics, Electrical Engineering, Mathematics or other quantitative fields.
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 information will be kept confidential according to EEO guidelines.