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Bayesian Networks Jobs in Boston, MA (NOW HIRING)

Amazon

Applied Scientist II - AMZ27057.1

Boston, MA · On-site

$161K - $193K/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.

Ameriprise Financial

Senior Data Scientist

Boston, MA · On-site

Competence using advanced statistical methods such as generalized regression models, Bayesian methods, random forest, gradient boosting, neural networks, machine learning, clustering, or similar ...

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Bayesian Networks information

What is the difference between Bayesian Networks vs Data Analysts?

AspectBayesian NetworksData Analysts
Required CredentialsStatistics, Data Science, Computer Science degrees; certifications in probabilistic modelingStatistics, Data Science, Business Analytics degrees; certifications in data analysis tools
Work EnvironmentResearch, modeling, and algorithm development in tech or research firmsData interpretation, reporting, and visualization across various industries
Industry UsageUsed for probabilistic reasoning, decision support, and machine learningUsed for data interpretation, reporting, and business insights

Bayesian Networks focus on probabilistic modeling and decision-making algorithms, often requiring advanced statistical knowledge. Data Analysts primarily interpret and visualize data to inform business decisions. While both roles involve data, Bayesian Networks are more technical and model-driven, whereas Data Analysts focus on data interpretation and reporting.

What are Bayesian Networks?

Bayesian Networks are probabilistic graphical models that represent a set of variables and their conditional dependencies using a directed acyclic graph. They are used to model uncertainty in complex systems by encoding relationships between variables and allowing for efficient inference and reasoning. These networks are widely applied in fields such as machine learning, diagnostics, decision support, and bioinformatics to help predict outcomes and understand causal relationships.

What are the key skills and qualifications needed to thrive as a Bayesian Networks Specialist, and why are they important?

To thrive as a Bayesian Networks Specialist, you need a strong background in statistics, probability theory, and machine learning, often supported by a degree in computer science, mathematics, or a related field. Proficiency with programming languages such as Python or R, and experience using specialized libraries like pgmpy or bnlearn, are typically required. Strong analytical thinking, problem-solving ability, and effective communication skills set standout professionals apart in this role. These competencies are crucial for designing, implementing, and interpreting Bayesian models that inform critical decision-making in complex domains.

What are some common challenges faced by professionals working with Bayesian Networks in real-world projects?

Professionals working with Bayesian Networks often encounter challenges such as handling incomplete or noisy data, defining accurate conditional dependencies, and ensuring computational efficiency for large or complex networks. Collaboration with domain experts is crucial to correctly structure the network and validate assumptions. Additionally, integrating Bayesian models with existing data systems and effectively communicating probabilistic results to non-technical stakeholders are important aspects of the role.
What are popular job titles related to Bayesian Networks jobs in Boston, MA? For Bayesian Networks jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Bayesian Networks jobs in Boston, MA look for? The top searched job categories for Bayesian Networks jobs in Boston, MA are:
Bayesian Networks jobs near you
Infographic showing various Bayesian Networks job openings in Boston, MA as of July 2026, with employment types broken down into 74% Full Time, and 26% Contract. Highlights an 74% In-person, and 26% Remote job distribution.
Data Scientist / Senior Data Scientist (Risk Modeling)

Data Scientist / Senior Data Scientist (Risk Modeling)

Berkshire Hathaway Specialty Insurance

Boston, MA • On-site

$100K - $160K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

Job description

Who are we?

A strategic and trusted insurance partner, Berkshire Hathaway Specialty Insurance (BHSI), provides a broad range of commercial property, casualty and specialty insurance coverages and outstanding service to customers and brokers around the world. Part of Berkshire Hathaway’s insurance operations, we bring our solutions to market with our stellar brand name, top-rated balance sheet, and the expertise of our global team of professionals, who exude excellent capabilities and strong character.


We are a values-based organization where respect, integrity, excellence, collaboration, and passion define who we are and how we do business. We value diversity of backgrounds, experience, and perspectives and strive to foster an inclusive environment that enables all our team members to bring their best selves to work. We are one team committed to building a culture where every teammate has the opportunity to contribute and be recognized. Want to be part of the team building the finest property, casualty and specialty lines insurance company in the world?


Learn more about our unique culture and history.


Job Opportunity:


Berkshire Hathaway Specialty Insurance (BHSI) has an exciting opportunity for Data Scientist / Senior Data Scientist to join the Catastrophe Engineering and Analytics (CAT E&A) team. CAT E&A is an innovative and versatile technical team conducting catastrophe risk research and development and providing complex quantitative metrics that inform underwriting decisions across multiple lines of business.


The successful candidate will be responsible for identifying and applying cutting-edge data science techniques to build a better view of the risk for multiple perils. You will work across functional areas and perils within the team, supporting the development of models for various natural catastrophes, natural hazards, building vulnerability, and man-made risks such as cyber, casualty, among others. In addition, you will conduct in-depth evaluation of vendor models, research and develop internal views of exposure and risks, consult on account-specific risk analyses, and develop internal tools to facilitate account underwriting decision-making and other related activities.


Duties & Responsibilities:


  • Evaluate and develop insights into large and diverse data sets from claims, hazard models, structural analysis, geospatial sources, and various other public/proprietary datasets.
  • Develop and maintain expertise in advanced data science, machine learning, and artificial intelligence techniques, and their application to understanding risk.
  • Work with domain experts across teams and perils to enhance our use of available data.
  • Propose and execute innovative solutions to insurance problems that directly impact BHSI underwriting decisions.


Qualifications, Skills and Experience:


Educational Background

  • Advanced degree (Master's or Ph.D.) in Statistics, Actuarial Science, Applied Mathematics, Data Science, Engineering, or other equivalent quantitative discipline.
  • Strong academic foundation in probability theory, statistical inference, stochastic processes, and Bayesian statistics.


Technical & Analytical Skills

  • Deep expertise in probability models commonly used in insurance (e.g., frequency–severity models, GLMs, loss distributions).
  • Strong applied statistics skills for:
    • Risk modeling
    • Predictive analytics
    • Pricing & underwriting analytics
    • Catastrophe exposure analysis
  • Proficiency in statistical and machine learning techniques, including:
    • Regression (GLM, GAM, GAMMs)
    • Time-series forecasting
    • Gradient boosting, random forests, and other tree-based models, neural networks models
    • Clustering and segmentation
    • Bayesian methods
  • Hands-on experience with key programming tools:
    • Python (NumPy, pandas, scikit-learn; PyTorch/TensorFlow a plus)
    • R (actuarial/statistical packages)
    • SQL for data extraction and manipulation
    • Familiarity with Git and Docker is a plus
  • Experience with big data and distributed computing (e.g., Spark, Databricks, AWS/GCP/Azure) is a plus.


Preferred Domain Knowledge in Risk Modeling

  • Strong understanding of property & casualty insurance, including:
    • Exposure modeling
    • Loss distributions (e.g., Pareto, lognormal, gamma)
    • Catastrophe risk concepts and tail modeling
    • Portfolio risk aggregation, reinsurance structures, and risk metrics (AAL, PML, TVaR)


Data Skills

  • Ability to work with large structured and unstructured datasets.
  • Expertise in data cleaning, transformation, and feature engineering.
  • Experience building automated data pipelines and scalable model workflows.


Modeling & Communication

  • Ability to translate complex statistical concepts into actionable business insights.
  • Experience communicating results clearly to actuaries, underwriters, executives, and non-technical stakeholders.
  • Strong documentation and model governance discipline.


Professional Competencies

  • Curious, analytical thinker with strong problem-solving ability.
  • Ability to work independently in ambiguous problem spaces.
  • Collaborative mindset — comfortable partnering with actuaries, underwriters, portfolio managers, and engineers.


BHSI Offers:


  • A competitive package and exciting growth opportunities for career-oriented teammates.
  • A dynamic, action oriented, and thoughtful environment centered on always doing the right thing for our customers, teammates, and our other stakeholders.
  • A purposely non-bureaucratic organization that embraces simplicity over complexity and emphasizes individual excellence in a team framework.
  • Benefits that support your life and well-being, which include:
    • Comprehensive Health, Dental and Vision benefits
    • Disability Insurance (both short-term and long-term)
    • Life Insurance (for you and your family)
    • Accidental Death & Dismemberment Insurance (for you and your family)
    • Flexible Spending Accounts
    • Health Reimbursement Account
    • Employee Assistance Program
    • Retirement Savings 401(k) Plan with Company Match
    • Generous holiday and Paid Time Off
    • Tuition Reimbursement
    • Paid Parental Leave


The base salary range for this position in Atlanta, GA, Boston, MA, or San Ramon, CA is $100,000 to $160,000, along with annual bonus eligibility. Total compensation for a candidate is determined by their relevant skills, location, and experience. We value our teammates – both their capabilities and character – as demonstrated by our amazing culture.


NOTE: Compensation will be commensurate with experience. This job description is not intended to be all-inclusive. Team Member may perform other related duties as negotiated to meet the ongoing needs of the organization.