Decision Science Analyst
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Before you apply
LocationIrving, TX, US
Typefull-time
SeniorityEntry
Experience1–3 yrs
DepartmentInformation Technology
Company size1,001–5,000 people
PostedSep 29, 2026 · 1mo ago
Verified live3d ago
At a glanceSummarised by Seekless from the posting.
Bachelor's degree with emphasis in Computer Science, Computer Information Systems or equivalent combination of education and work experience
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
Exposure to MLOps and model lifecycle management
Skills
Azure AI
Databricks
SQL
Python
R
Large Language Models (LLMs)
RAG
MCP
Machine Learning
MLOps
Company Details
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.
Responsibilities
The Decision Science Analyst plays a key role in transforming raw data into actionable business insights that inform strategic decision-making across the organization. This position will work closely with cross-functional teams including Underwriting, Claims, Finance, and Actuarial to support data-driven initiatives and improve operational outcomes. Responsibilities
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Analyze, cleanse, and transform large datasets to support strategic and operational business decision-making.
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Leverage Azure AI and Databricks to build scalable data pipelines and analytical models.
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Partner with business and technology teams to evaluate, implement, and integrate Large Language Models (LLMs) into business processes and workflows.
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Translate complex data findings into clear, meaningful, and actionable insights for stakeholders across underwriting, claims, finance, and actuarial departments.
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Support experimentation and model development for predictive analytics and machine learning initiatives.
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Document analytical methodologies, data sources, processes, and findings to ensure transparency, consistency, and reproducibility.
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Stay informed on emerging trends in analytics, artificial intelligence, and decision science to recommend innovative solutions.
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Perform other duties as assigned.
Qualifications
Education Bachelor’s degree with emphasis in Computer Science, Computer Information Systems or equivalent combination of education and work experience will be considered. Qualifications
•
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.
Additional Company Details
Legal
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 Details
Sponsorship not Offered for this Role