ZipRecruiter

Log In

1

Bayesian Modeling Jobs in Watertown, MA (NOW HIRING)

Costello Medical

Statistician Intern

Boston, MA · On-site

$54K - $66K/yr

  • Medical

  • Dental

  • Vision

  • PTO

... 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 ...

Atavistik Bio

Sr. Director, Biostatistics

Cambridge, MA · On-site

$270K - $290K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

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 ...

Atavistik Bio

Sr. Director, Biostatistics

Cambridge, MA · On-site

$270K - $290K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

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 ...

Analog Devices

Post-Silicon Validation Engineer

Wilmington, MA · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... Bayesian methods) - Time-series and waveform analysis techniques - Agentic AI systems for lab ... modeling, Pattern recognition & Anomaly detection • Experience using or integrating AI-enabled ...

Atavistik Bio

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 ...

Fidelity Investments

AM Quantitative Analyst I

Boston, MA

$135K - $175K/yr

... 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 ...

Varsity Tutors

Statistics Graduate Level Tutor

Lynn, MA · Remote

$18 - $40/hr

... Bayesian inference, regression analysis, multivariate methods, experimental design, and ... Ability to explain asymptotic theory, Neyman-Pearson lemma, and generalized linear models while ...

Amgen

Senior Director - BioIntelligence

Cambridge, MA

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Advance modeling approaches using modern AI techniques such as: * protein language models * generative modeling and inverse folding * representation learning * active learning and Bayesian ...

previous page

Showing results 41-60

All JobsBayesian Modeling JobsBayesian Modeling Jobs in Watertown, MA

Bayesian Modeling information

See Watertown, MA salary details

$11

$63

$90

How much do bayesian modeling jobs pay per hour?

As of Aug 14, 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.
Bayesian Modeling jobs near you

AI for Quantum Operations Lead

QuEra Computing, Inc.

Boston, MA • On-site

Full-time

Re-posted 6 days ago

Job description

Role Summary

The AI for Quantum Operations Lead owns the roadmap and execution strategy for AI-assisted calibration, diagnostics, prediction, and recovery across quantum systems, ensuring that AI improves machine uptime, calibration speed, and operator decision-making while deterministic control and safety software remain authoritative.

Key Responsibilities

  • Define and drive the AI operations roadmap across calibration optimization, atom image/readout analysis, drift prediction, root-cause diagnosis, and recovery recommendation.
  • Partner with quantum systems, controls, software, hardware, and ML teams to identify high-value workflows where AI can safely propose, rank, predict, or optimize.
  • Establish the bounded-AI operating model: AI provides recommendations or constrained optimizations, while deterministic control software enforces timing, hardware limits, validation, rollback, and safety logic.
  • Prioritize AI pilots for Quokka, Calibration Manager, telemetry systems, readout pipelines, and QPU operations workflows.
  • Own requirements for dataset traceability, model validation, observability, offline replay, deployment gates, and operator-facing explainability.
  • Translate machine-performance pain points into measurable AI/ML objectives such as reduced calibration time, fewer failed jobs, faster recovery, improved readout quality, and better drift detection.
  • Coordinate cross-functional execution, staffing needs, milestones, risk reviews, and stakeholder communication.

Required Background

  • Strong technical leadership experience in AI/ML, controls, robotics, scientific instrumentation, or complex hardware operations.
  • Experience bringing ML models into production environments where reliability, safety, traceability, and human/operator trust matter.
  • Ability to work across software, hardware, physics, and operations teams.
  • Strong systems thinking; understands where AI should help, where deterministic software must remain in charge, and how to design the boundary between them.

Preferred Background

  • Experience with Bayesian optimization, active learning, time-series forecasting, computer vision, anomaly detection, or root-cause analysis.
  • Familiarity with calibration workflows, lab automation, telemetry systems, or hardware-in-the-loop validation.
  • Exposure to quantum computing, neutral atoms, optical systems, embedded control, or real-time systems.

Success Measures

  • Clear AI operations roadmap with owners, milestones, and safety gates.
  • First bounded AI pilots deployed into calibration or readout workflows.
  • Measurable reduction in calibration effort, diagnosis time, drift-related failures, or recovery time.
  • Strong governance around model validation, data provenance, deployment approval, and operator trust.

QuEra is committed to cultivating a diverse work environment and is proud to be an equal opportunity employer. We highly value diversity in our current and future employees and do not discriminate (including in our hiring and promotion practices) based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.

Apply