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Predictive Modeler Jobs (NOW HIRING)

Predictive Analytics Consultant

$69.80K - $110.30K/yr

The position will focus on building, testing, validating, and deploying predictive and optimization models that support credit underwriting decisions. The consultant will develop data-driven ...

This role designs and develops predictive models (e.g., for performance, turnover, and hiring outcomes), automates data integration between spreadsheets and HR systems, and builds robust data ...

Model Development: Assist the principal data scientist in developing and tuning predictive models (e.g., predicting equipment failure, estimating lead times, or optimizing inventory levels). * Data ...

This role designs and develops predictive models (e.g., for performance, turnover, and hiring outcomes), automates data integration between spreadsheets and HR systems, and builds robust data ...

Model Development: Assist the principal data scientist in developing and tuning predictive models (e.g., predicting equipment failure, estimating lead times, or optimizing inventory levels). * Data ...

Statistical Modeler

Los Angeles, CA ยท On-site

$59 - $76.50/hr

Use predictive modeling, SQL, python, and a machine learning engineering pipeline to deliver this. Enhance this model with additional accuracy enhancements including a price The model pipeline is set ...

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Predictive Modeler information

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$10

$58

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How much do predictive modeler jobs pay per hour?

As of Jun 1, 2026, the average hourly pay for predictive modeler in the United States is $58.71, according to ZipRecruiter salary data. Most workers in this role earn between $52.64 and $68.27 per hour, depending on experience, location, and employer.

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

To thrive as a Predictive Modeler, you need a strong background in statistics, mathematics, and data analysis, often supported by a degree in a quantitative field such as statistics, mathematics, or computer science. Familiarity with programming languages like Python or R, experience with machine learning frameworks, and knowledge of data visualization tools are typically required. Analytical thinking, problem-solving, and effective communication are standout soft skills for translating complex data into actionable insights. These skills and qualities are crucial for building accurate models that drive informed business decisions and add strategic value.

How does a Predictive Modeler typically collaborate with data scientists and business stakeholders during a project?

Predictive Modelers work closely with data scientists to ensure that models are statistically sound and meet technical requirements, often sharing insights on data preprocessing and feature engineering. They also collaborate with business stakeholders to understand project goals, translate business problems into analytical tasks, and explain model outcomes in accessible terms. Regular communication and feedback loops help ensure that the developed models align with business objectives and deliver actionable insights. This collaborative approach is essential for successful project delivery and for ensuring that predictive solutions provide real value.

What are predictive modelers?

Predictive modelers are professionals who use statistical techniques, machine learning, and data analysis to develop models that forecast future outcomes based on historical data. They work in various industries, such as finance, healthcare, and marketing, to help organizations make data-driven decisions and anticipate trends or risks. Predictive modelers typically use tools like Python, R, or specialized software, and their work can involve data cleaning, selecting appropriate algorithms, and validating model performance. Their insights help businesses optimize processes, reduce costs, and improve customer satisfaction.

What is the difference between Predictive Modeler vs Data Analyst?

AspectPredictive ModelerData Analyst
Required CredentialsBachelor's or Master's in Statistics, Data Science, or related fields; often certifications in modeling or analyticsBachelor's in Statistics, Data Analysis, or related fields; certifications in data visualization or analysis tools
Work EnvironmentData science teams, analytics departments, often in tech, finance, or healthcare industriesBusiness units, marketing, finance, or operations teams across various industries
Employer & Industry UsageUsed for building predictive models to forecast trends and behaviorsUsed for interpreting data, generating reports, and providing insights

While both roles analyze data, Predictive Modelers focus on creating models to forecast future outcomes, whereas Data Analysts interpret existing data to inform decisions. Predictive Modelers typically require advanced statistical skills and modeling expertise, making their role more specialized in predictive analytics.

More about Predictive Modeler jobs
What cities are hiring for Predictive Modeler jobs? Cities with the most Predictive Modeler job openings:
What states have the most Predictive Modeler jobs? States with the most job openings for Predictive Modeler jobs include:
What are popular job titles related to Predictive Modeler jobs? For Predictive Modeler jobs, the most frequently searched job titles are:
Infographic showing various Predictive Modeler job openings in the United States as of May 2026, with employment types broken down into 94% Full Time, 4% Part Time, 1% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $122,123 per year, or $58.7 per hour.

Predictive Modeling & Risk Scientist

Cover Whale Insurance Solutions

New York, NY โ€ข Remote

$128K - $185K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Who is Cover Whale?

Cover Whale is the nationโ€™s leading commercial trucking insurtech. We improve road safety by combining the insurance products we sell with our telematics-based, data-driven driver coaching and safety program known as DriveSmart. Our program is proven to save lives while delivering better insurance for our drivers. For more information, please visit www.coverwhale.com. Join us in the mission!

The Role:

We are seeking a highly analytical, technically strong Actuarial/Data Science professional to own and evolve our end-to-end reserving and predictive modeling capabilities. This role will maintain and enhance our Python-based reserving models while building predictive models using live telematics and claims data to drive pricing, cancellation strategy, and large loss detection. The position sits at the core of our underwriting and growth strategy, directly influencing dynamic pricing, loss ratio performance, and profitable expansion. This is a very exciting and high-impact job that involves a lot of thinking, research, and creativity.

Please note: Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Responsibilities:

  • Own and continuously improve the end-to-end reserving process, including maintaining and enhancing Python-based reserving models to improve accuracy and efficiency.
  • Develop and deploy predictive models using telematics, claims, and policy data to improve pre-bind and post-bind risk selection, with measurable impact on ULR and cancellation performance.
  • Build and refine large loss models using claims notes and historical data to improve early identification of high-risk claims.
  • Design and implement dynamic pricing frameworks and capabilities leveraging live market and portfolio data.
  • Translate complex data insights into clear actionable business recommendations for underwriting, growth, and leadership teams.
  • Produce carrier-level reporting deliverables and analytical outputs that meet high-quality and compliance standards.
  • Create agency-level and geographic performance insights to guide growth strategy and strategic initiatives.
  • Automate recurring analyses and reporting workflows to increase speed, scalability, and reliability.

Requirements

  • Experience with insurance analytics, actuarial modeling, or predictive risk modeling in the insurance industry.
  • Strong proficiency in Python for statistical modeling and data analysis.
  • Comfortable leveraging AI-assisted coding tools (Claude, Copilot, etc.) while critically validating outputs.
  • Experience working with large-scale datasets and building production-grade analytical models.
  • Demonstrated experience with actuarial reserving models or insurance forecasting methodologies.
  • Experience applying machine learning techniques such as regression models, gradient boosting, classification models, or anomaly detection.
  • Ability to design models that influence pricing, underwriting decisions, and portfolio risk management.
  • Strong SQL and data manipulation skills.
  • Experience building automated analytical pipelines or reporting workflows.

Soft skills: Curious, hard-working, thinking outside of the box, creative, attention to detail, and use of Claude code.

Preferred Qualifications: Actuary, Mathematics, Big Four consulting experience.

Candidates advancing through the interview process may be asked to complete a brief work exercise related to predictive modeling and risk analysis. The exercise is designed to reflect real-world challenges relevant to the role. Candidates completing this step will receive reasonable compensation for their time.

Benefits

Compensation:

The Expected base pay for the role will be $128,000 - $185,000 at the commencement of employment. However, base pay if hired will be determined on an individualized basis and depends on the geographical location, years of experience, etc. and is only part of the total compensation package, which, depending on the position, may also include discretionary bonus and other Cover Whale-sponsored total rewards/benefits.

Perks/Benefits:

  • Health Care Plan (Medical, Dental & Vision)
  • Retirement Plan (401k) match
  • Wellness benefits, including EAP, Gym Reimbursement, etc.
  • Life Insurance (Basic, Voluntary & AD&D)
  • Paid Time Off (Vacation, Sick & Public Holidays)
  • Paid Family Leave (Maternity, Paternity)
  • Tuition Assistance
  • Professional Training & Development