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Lead Actuarial Predictive Modeler

Costa Mesa, CA · On-site

$145K - $194K/yr

Master's degree in Actuarial, Statistical, or Data Science field (or equivalent combination of education and experience) required * Demonstrated success implementing predictive modeling solutions for ...

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How much do data scientist predictive modeler jobs pay per year?

As of Jun 6, 2026, the average yearly pay for data scientist predictive modeler in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What does a Data Scientist Predictive Modeler do?

A Data Scientist Predictive Modeler uses statistical techniques, machine learning algorithms, and data analysis tools to identify patterns in data and make predictions about future outcomes. They gather and clean data, build predictive models, and interpret the results to help organizations make data-driven decisions. Their work is applied in areas such as customer behavior forecasting, risk assessment, and process optimization. They often collaborate with business stakeholders to translate insights into actionable strategies.

What is the difference between Data Scientist Predictive Modeler vs Data Analyst?

AspectData Scientist Predictive ModelerData Analyst
CredentialsBachelor's or Master's in Data Science, Statistics, or related fieldsBachelor's in Data Analysis, Statistics, or related fields
Work EnvironmentDevelops predictive models, uses advanced analytics, often in tech or finance industriesAnalyzes data sets, creates reports, supports decision-making across various industries
Employer UsageUsed by organizations focusing on predictive analytics and machine learningUsed by companies needing data reporting and basic analysis

While both roles work with data, a Data Scientist Predictive Modeler specializes in building predictive models and advanced analytics, whereas a Data Analyst focuses on interpreting data and generating reports. The Predictive Modeler role requires more technical skills in machine learning and statistical modeling, making it suitable for organizations aiming to forecast trends and automate decision processes.

What are some common challenges faced by Data Scientist Predictive Modelers when deploying models into production environments?

Data Scientist Predictive Modelers often encounter challenges when transitioning models from development to production. These challenges can include ensuring that models perform consistently on real-world data, handling data pipeline integration, and addressing changes in data patterns (data drift) over time. Additionally, collaborating closely with engineering teams is crucial to optimize model scalability and maintainability. Clear documentation, robust testing, and ongoing monitoring are essential practices to successfully address these challenges and ensure long-term model performance.

What are the key skills and qualifications needed to thrive as a Data Scientist Predictive Modeler, and why are they important?

To thrive as a Data Scientist Predictive Modeler, you need a strong background in statistics, machine learning, and data analysis, often supported by a degree in computer science, mathematics, or a related field. Proficiency in programming languages such as Python or R, experience with data visualization tools, and familiarity with machine learning libraries like scikit-learn or TensorFlow are typically required. Strong problem-solving abilities, effective communication, and a collaborative mindset are crucial soft skills that set top performers apart. These skills and qualifications are vital for building accurate predictive models, translating data insights into actionable business strategies, and effectively communicating findings to stakeholders.
More about Data Scientist Predictive Modeler jobs
What cities are hiring for Data Scientist Predictive Modeler jobs? Cities with the most Data Scientist Predictive Modeler job openings:
What job categories do people searching Data Scientist Predictive Modeler jobs look for? The top searched job categories for Data Scientist Predictive Modeler jobs are:
Data Scientist Predictive Modeler jobs near you
Infographic showing various Data Scientist Predictive Modeler job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Senior Data Scientist - Predictive Analytics

Great American Insurance Group

Cincinnati, OH • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 16 days ago

Great American Insurance Group rating

8.8

Company rating: 8.8 out of 10

Based on 27 frontline employees who took The Breakroom Quiz

52nd of 260 rated insurance

Job description

Be Here. Be Great. Working for a leader in the insurance industry means opportunity for you. Great American Insurance Group's member companies are subsidiaries of American Financial Group. We combine a "small company" culture where your ideas will be heard with "big company" expertise to help you succeed. With over 30 specialty and property and casualty operations, there are always opportunities here to learn and grow.
At Great American, we value and recognize the benefits derived when people with different backgrounds and experiences work together to achieve business results. Our goal is to create a workplace where all employees feel included, empowered, and enabled to perform at their best.
Join our Predictive Analytics team within the Business Data & Analytics department! opportunity to work within a highly collaborative team of data professionals focused on solving critical business challenges in the insurance industry. The roles emphasize intellectual growth, innovation, and the practical application of cutting-edge AI technologies to drive business value.
Great American Insurance Group is committed to fostering professional growth through exposure to emerging technologies, cross-functional collaboration, and opportunities to contribute to strategic AI initiatives that shape the future of the insurance industry.
This position is located in our Cincinnati office and will work on a hybrid schedule. Great American's culture is built on connection, shared learning, and strong relationships. To support this, employees in this role are expected to be on-site four days a week, with the flexibility to work one day remotely. Core in-office days are Tuesday-Thursday, with the fourth day determined by business needs.
Essential Job Functions and Responsibilities
  • Leads the analysis of large, complex datasets to identify advanced trends, patterns, and strategic opportunities
  • Architects and leads the design, development, and deployment of sophisticated predictive models for underwriting, pricing, claims, and customer retention
  • Serves as technical lead for advanced LLM implementations, including custom transformer architectures, advanced fine-tuning strategies, and novel generative AI applications
  • Designs and implements complex RAG and Agentic systems with multi-modal capabilities and advanced reasoning
  • Designs and develops evaluation pipelines to assess the quality and effectiveness of Generative AI outputs
  • Leads Vision Language Model initiatives and advanced computer vision projects using OpenCV and cutting-edge Vision AI technologies
  • Mentors junior data scientists and provides technical guidance on complex modeling projects
  • Drives innovation by exploring new data sources, advanced modeling techniques, and emerging AI technologies
  • Collaborates with senior leadership and cross-functional teams to translate complex business challenges into scalable AI solutions
  • Designs and implements enterprise-level data pipelines and automated reporting tools
  • Establishes model governance frameworks and ensures compliance with regulatory requirements
  • Communicates complex technical concepts and strategic recommendations to C-level executives through compelling presentations
  • Monitors and optimizes model performance across the enterprise and ensures data quality at scale
  • May have responsibility for performance coaching of staff and participatory role in talent selection and development
  • Drives AI strategy and roadmap development for the Predictive Analysis team
  • Performs other duties as assigned

Job Requirements
  • Education: Bachelor's degree in Computer Science, Computer Engineering, Data Science, Statistics, or related quantitative field required. Master's or PhD in related field strongly preferred.

  • Experience: 5-6 years of progressive experience in data science and machine learning, with at least 2 years leading complex AI/ML projects and mentoring junior team members.

Required Technical Skills:
  • Advanced Generative AI & LLM Leadership: • Expert-level knowledge of Large Language Models and generative AI architectures • Advanced experience with transformer models, attention mechanisms, and custom model development • Proven track record in BERT, GPT, and other foundation model implementations • Advanced fine-tuning techniques including LoRA, QLoRA, and parameter-efficient methods • Expert-level RAG system design and Agentic RAG implementation • Experience with multi-agent systems and AI orchestration frameworks

  • Advanced Vision AI & Computer Vision: • Expert proficiency in OpenCV and advanced computer vision techniques • Leadership experience with Vision Language Models and multi-modal AI systems • Advanced image processing, object detection, and video analysis • Integration of vision, language, and reasoning capabilities

  • Senior Technical Leadership: • Expert Python programming with deep knowledge of AI/ML ecosystems • Advanced experience with PyTorch, TensorFlow, and HuggingFace transformers • Database optimization and advanced SQL techniques • MLOps and model lifecycle management

  • Cloud & Enterprise Data Platforms: • Advanced Microsoft Azure architecture and AI services • Expert-level Snowflake implementation including: - Advanced Snowflake SQL and performance optimization - Snowflake Cortex AI/ML advanced features and custom implementations - Snowflake Intelligence advanced analytics and semantic search optimization - Snowflake data sharing and marketplace integration • Enterprise data pipeline architecture and governance

  • Leadership & Strategic Competencies: • Advanced statistical modeling and mathematical foundations • Enterprise model deployment and production optimization • Advanced data visualization and executive-level presentation skills • Deep understanding of insurance industry regulations and model governance • Proven leadership and mentoring abilities • Strategic thinking and AI roadmap development • Cross-functional collaboration and stakeholder management

Scope of Job/Qualifications:
Leads complex to large-scale AI/ML projects with enterprise impact. Proven expertise in optimizing advanced models and implementing cutting-edge machine learning solutions. Demonstrates deep understanding of the organization's business and technology operations with ability to drive strategic AI initiatives. Shows comprehensive knowledge of industry trends, regulatory requirements, and emerging technologies in insurance and AI.
Business Unit:
Business Data and Analytics
Benefits:
We offer competitive benefits packages for full-time and part-time employees*. Full-time employees have access to medical, dental, and vision coverage, wellness plans, parental leave, adoption assistance, and tuition reimbursement. Full-time and eligible part-time employees also enjoy Paid Time Off and paid holidays, a 401(k) plan with company match, an employee stock purchase plan, and commuter benefits.
Compensation varies by role, level, and location and is influenced by skills, experience, and business needs. Your recruiter will provide details about benefits and specific compensation ranges during the hiring process. Learn more at http://www.gaig.com/careers.
*Excludes seasonal employees and interns.

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