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Bayesian Modeling Jobs in Massachusetts (NOW HIRING)

Understand Bayesian modeling techniques. * Are capable of analyzing data and making rigorous statements about what can or cannot be concluded. * Have experience designing and implementing model ...

Experience with Bayesian modeling and inference techniques for decision making under uncertainty. * Experience with the Bazel build framework The salary range for this role is an estimate based on a ...

Experience with machine learning techniques (such as Bayesian modeling and inference techniques) for decision making under uncertainty. * Experience with the Bazel build framework The salary range ...

Principal Engineer Motion Planning

Boston, MA · On-site +1

$240K - $330K/yr

Experience with machine learning techniques (such as Bayesian modeling and inference techniques) for decision making under uncertainty. * Experience with the Bazel build framework The salary range ...

Applied Scientist III - AMZ9898584

Boston, MA · On-site

$167.10K - $226.10K/yr

Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data ...

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Bayesian Modeling information

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 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 popular job titles related to Bayesian Modeling jobs in Massachusetts? For Bayesian Modeling jobs in Massachusetts, the most frequently searched job titles are:
What cities in Massachusetts are hiring for Bayesian Modeling jobs? Cities in Massachusetts with the most Bayesian Modeling job openings:

Principal Product Manager - Agentic Media Measurement

Newton Research

Boston, MA

$180K - $230K/yr

Other

Posted 7 days ago


Job description

Principal Product Manager - Agentic Media MeasurementCompany Description

Newton Research is a fast-growing software start-up founded by repeat entrepreneurs and well-funded by blue chip venture capital firms. We are building the next generation of the closed loop media lifecycle, developing AI agents that leverage the latest in LLMs and generative AI with specialized knowledge. Our products generate actionable business insights for our customers and partners, assisting in each step of the media planning, buying and measurement lifecycle.

About the Role

As Principal Product Manager - Agentic Media Measurement, you will own the strategy, roadmap, and execution of Newton's measurement and insights platform-the analytical engine that proves media works and tells brands where to invest next. Your work will sit at the intersection of causal inference, Bayesian modeling, and modern AI, turning complex marketing science into products that deliver clear, defensible answers to the questions CMOs and media teams ask every day.

You will lead the product direction for Newton's Marketing Mix Modeling (MMM), Multi-Touch Attribution (MTA), and cross-channel measurement capabilities, working hand-in-hand with our data science team to translate advanced statistical and causal AI techniques into intuitive, scalable products. You will collaborate directly with brand marketers, agency measurement leads, and senior executives at our customers and partners to deeply understand how measurement drives real media decisions-and where current solutions fall short.

This role is not about shipping dashboards-it's about building the measurement intelligence layer that makes autonomous media optimization possible, from foundational methodology to market-defining product experiences.

What You Will Do
  • Lead the product vision and roadmap for Newton's agentic measurement offerings and models, spanning MMM, MTA, incrementality testing, and cross-channel insights
  • Deeply understand customer measurement workflows through direct discovery, data, and experimentation; translate insights into clear product requirements and hypotheses
  • Partner closely with data science to shape modeling approaches-including Bayesian MMM, causal inference (e.g., PCMCI+), adstock modeling, and incrementality frameworks-ensuring methodological rigor translates into usable, trustworthy products
  • Define how measurement intelligence feeds Newton's agentic capabilities, closing the loop between insights and autonomous media optimization
  • Rapid-prototype new measurement features and insight experiences, demo them to customers weekly, and iterate relentlessly based on quantitative usage data and qualitative feedback
  • Own the end-to-end product lifecycle-from concept to launch to iteration-tracking KPIs, model performance metrics, and usage analytics to inform prioritization
  • Collaborate with marketing, sales, and customer success on positioning, packaging, and GTM plans that differentiate Newton's measurement story and accelerate adoption
  • Lead cross-functional squads, driving crisp execution in an Agile product development lifecycle
  • Stay current on measurement industry evolution-privacy changes, signal loss, walled garden reporting, emerging standards-and translate those shifts into product strategy
What Makes You a Great Fit
  • 5-8 years of hands-on experience in marketing measurement, analytics, or marketing science-including direct work with MMM, MTA, incrementality testing, or media effectiveness methodologies
  • 5+ years of product management experience, with 2+ years building measurement, analytics, or AI/ML products at scale
  • Solid understanding of statistical modeling concepts (Bayesian methods, causal inference, regression, time-series analysis) and the ability to engage credibly with data scientists on methodology choices
  • Experience with multi-channel media environments-understanding how paid search, social, programmatic, CTV, retail media, and offline channels interact in a measurement framework
  • Familiarity with the practical challenges of measurement: data gaps, attribution bias, signal loss from privacy regulations, walled garden limitations, and cross-device reconciliation
  • Strong ability to define, communicate, and execute a product vision across business and technical stakeholders
  • Experience working with agency measurement teams, brand analytics groups, or marketing science consultancies is a strong plus
  • Passion for marketing science, media analytics, and the adtech/martech ecosystem
  • Excellent written and verbal communication skills-you simplify complexity, influence customers, and inspire teams

Salary range: $180,000-$230,000 + equity