At Berkley Entertainment, we have over 25 years of underwriting risks in Entertainment & Sports.  Our one focus is entertainment insurance. We bring our decades of entertainment experience together to go beyond the basics, providing crafted coverage solutions to protect our clients.

 

Our team’s industry experience and collaborative approach leads to great client solutions — and this is by design. We are here to assist with customizing products and services that are tailored to respond to each client’s unique exposures.

• Analyze, cleanse, and transform large datasets to support strategic and operational business decision-making.
• Leverage Azure AI and Databricks to build scalable data pipelines and analytical models.
• Partner with business and technology teams to evaluate, implement, and integrate Large Language Models (LLMs) into business processes and workflows.
• Translate complex data findings into clear, meaningful, and actionable insights for stakeholders across underwriting, claims, finance, and actuarial departments.
• Support experimentation and model development for predictive analytics and machine learning initiatives.
• Document analytical methodologies, data sources, processes, and findings to ensure transparency, consistency, and reproducibility.
• Stay informed on emerging trends in analytics, artificial intelligence, and decision science to recommend innovative solutions.
• Perform other duties as assigned.

• 1-3 years of experience in data analytics, decision science, or a related field.
• Proficiency in data cleaning and transformation techniques.
• Strong experience with Azure AI and Databricks.
• Familiarity with LLM integration and prompt engineering.
• Solid understanding of statistical analysis and data visualization.
• Proficiency in SQL, and Python or R for advanced analytics.
• Excellent communication and storytelling skills using data.
• Demonstrable experience with RAG / MCP implementation.
• Experience with machine learning models, including training, validation, and deployment, preferred.
• Exposure to MLOps and model lifecycle management, preferred.

The Company is an equal employment opportunity employer.

We do not accept any unsolicited resumes from external recruiting agencies or firms.

The company offers a competitive compensation plan and robust benefits package for full time regular employees.

The actual salary for this position will be determined by a number of factors, including the scope, complexity and location of the role; the skills, education, training, credentials and experience of the candidate; and other conditions of employment.

Sponsorship not Offered for this Role