> Markdown version of [/jobs/ext/4614890-data-scientist-senior-data-scientist-risk-modeling](https://www.wearedevelopers.com/jobs/ext/4614890-data-scientist-senior-data-scientist-risk-modeling). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Scientist / Senior Data Scientist (Risk Modeling)

- **Company:** Berkshire Hathaway
- **Location:** Boston, MA, United States
- **Experience:** Expert
- **Salary:** $100,000.0 - $160,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Artificial Neural Networks, Microsoft Azure, Big Data, Cluster Analysis, Data Cleansing, Data Mining, Programming Tools, Distributed Systems, Generalized Linear Model, Python (Programming Language), Machine Learning, NumPy, Tensorflow, SQL Databases, Pytorch, Random Forest, Apache Spark, Git, Pandas, Scikit Learn, Tree-based Models, Data Pipelines, Docker, Databricks
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/7_C9D931D55A75455C7AC48828361669B7

## About the Role

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 BackgroundAdvanced 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 SkillsDeep expertise in probability models commonly used in insurance (e.g., frequency-severity models, GLMs, loss distributions).Strong applied statistics skills for:Risk modelingPredictive analyticsPricing & underwriting analyticsCatastrophe exposure analysisProficiency in statistical and machine learning techniques, including:Regression (GLM, GAM, GAMMs)Time-series forecastingGradient boosting, random forests, and other tree-based models, neural networks models Clustering and segmentationBayesian methodsHands-on experience with key programming tools:Python (NumPy, pandas, scikit-learn; PyTorch/TensorFlow a plus)R (actuarial/statistical packages)SQL for data extraction and manipulationFamiliarity with Git and Docker is a plusExperience with big data and distributed computing (e.g.,
Spark, Databricks, AWS/GCP/Azure) is a plus.Preferred Domain Knowledge in Risk ModelingStrong understanding of property & casualty insurance, including:Exposure modelingLoss distributions (e.g., Pareto, lognormal, gamma)Catastrophe risk concepts and tail modelingPortfolio risk aggregation, reinsurance structures, and risk metrics (AAL, PML, TVaR)Data SkillsAbility 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 & CommunicationAbility 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 CompetenciesCurious, analytical thinker with strong problem-solving ability.Ability to work independently in ambiguous problem

## Description

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 cultureandhistory.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.