Insight Global

Data Scientist

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist with 3-5 years in insurance operations, 2-5 years in risk, geospatial, or statistical modeling, and proven machine learning deployment experience. Remote position; requires strong collaboration and data quality skills. Pay rate and contract length unspecified.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
December 23, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Remote
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
San Antonio, Texas Metropolitan Area
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🧠 - Skills detailed
#"ETL (Extract #Transform #Load)" #Data Science #Data Quality #Data Analysis #Model Validation #Data Engineering #ML (Machine Learning) #Python #Monitoring #SQL (Structured Query Language)
Role description
Required Skills & Experience • Minimum of 3-5 years of experience in an operations role within the insurance industry. • 2-5 years of experience in one or more of the following areas: • Risk Modeling • Geospatial Modeling • Statistical/ML Modeling • Proven experience building and deploying machine learning models in a production environment. • Demonstrated ability to solve complex data problems with limited initial information. • Experience working effectively in a collaborative environment with diverse stakeholders. • Exceptional attention to detail and commitment to data quality. Nice to Have Skills & Experience • Hands-on experience with risk modeling techniques. • Data engineering experience • Expertise in deploying machine learning models using industry-standard tools and platforms. • Understanding of P&C insurance principles and practices. • Ability to navigate and extract insights from ambiguous and unstructured data. • Excellent communication and interpersonal skills for effective collaboration. • A meticulous approach to data analysis and model validation. Job Description Insight Global is looking for a mid-level Data Scientist. This person will sit remotely and responsibilities include: develop and implement data-driven solutions to improve underwriting performance. Experiment with various data sources and statistical modeling techniques. Automate statistical model monitoring and data analysis. Document and publish model monitoring reports utilizing markdown or similar software. Version, publish, and maintain model monitoring code utilizing SQL and python. Prototype, test, and deploy machine learning models into production. Collaborate with stakeholders across the organization to identify and address key business and technical challenges. Work with ambiguous data to derive meaningful insights and create actionable recommendations.