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Predictive Modeling Jobs (NOW HIRING)

Design, architect, and maintain robust, scalable predictive modeling data pipelines across our data science ecosystem. * Design, develop, and maintain internal tooling that accelerates productivity ...

Design, architect, and maintain robust, scalable predictive modeling data pipelines across our data science ecosystem. * Design, develop, and maintain internal tooling that accelerates productivity ...

Senior Data Engineer, Predictive Modeling

Tempe, AZ · On-site

$101K - $137K/yr

Design, architect, and maintain robust, scalable predictive modeling data pipelines across our data science ecosystem. * Design, develop, and maintain internal tooling that accelerates productivity ...

Predictive Modeler

Lansing, MI · Hybrid

$55.50 - $72/hr

Auto-Owners Insurance, a top-rated insurance carrier, is seeking a predictive modeler to join our ... An understanding of statistical modeling or data science concepts, especially clustering ...

Predictive Modeler

Lansing, MI · On-site

$55.50 - $72/hr

Auto-Owners Insurance, a top-rated insurance carrier, is seeking a predictive modeler to join our ... An understanding of statistical modeling or data science concepts, especially clustering ...

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 ...

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Predictive Modeling information

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How much do predictive modeling jobs pay per hour?

As of Jul 2, 2026, the average hourly pay for predictive modeling 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 is the highest paying modeling job?

In predictive modeling, senior data scientists and machine learning engineers typically earn the highest salaries, often exceeding six figures annually. These roles require advanced skills in statistical analysis, programming, and experience with tools like Python or R, and they are often found in industries such as finance, technology, and healthcare.

What are the key skills and qualifications needed to thrive in the Predictive Modeling position, and why are they important?

To thrive in Predictive Modeling, you need strong statistical analysis, data mining, and machine learning skills, often supported by a degree in statistics, computer science, mathematics, or a related field. Expertise with tools such as Python, R, SAS, or SQL, as well as knowledge of data visualization software, is commonly required, and certifications in data science or analytics are a plus. Strong problem-solving abilities, attention to detail, and effective communication are key soft skills for this role. Mastering these skills enables professionals to build accurate models, interpret data-driven results, and clearly communicate insights to stakeholders, which are critical for informed business decision-making.

What is a Predictive Modeling job?

A Predictive Modeling job involves using statistical techniques, machine learning algorithms, and data analysis to forecast future outcomes based on historical data. Professionals in this role build and test models to identify patterns, trends, and relationships in complex datasets. They commonly work in industries like finance, healthcare, and marketing to improve decision-making and optimize business processes. Strong skills in programming, data manipulation, and statistical analysis are essential for success in this role.

What is a predictive modeler?

A predictive modeler is a professional who develops statistical and machine learning models to forecast future outcomes based on historical data. They use tools like Python, R, or SAS and often require strong analytical skills and knowledge of data science techniques. Their work supports decision-making in various industries such as finance, marketing, and healthcare.

Is 40 too late for data science?

Predictive modeling is a key role in data science, and age is not a barrier to entering the field. Many professionals transition into data science later in their careers by developing skills in programming, statistics, and tools like Python or R, often through online courses or certifications. Success depends on your ability to learn and apply relevant skills, regardless of age.

What does a typical workday look like for someone working in predictive modeling?

A typical day in predictive modeling involves gathering and cleaning data, selecting relevant features, and building statistical or machine learning models to forecast trends or behaviors. You’ll regularly use programming languages and analytics tools to test model performance and iterate on results, while documenting findings and preparing reports for internal teams or clients. Collaboration is often required with data engineers, subject matter experts, and business leaders to ensure that models align with organizational goals. Additionally, you may be tasked with presenting your insights to both technical and non-technical audiences, making strong communication skills essential for success in this role.

What jobs will no longer exist in 2030?

Predictive modeling roles may decline as automation and AI tools increasingly handle data analysis and forecasting tasks. Jobs that involve routine, repetitive tasks are also at risk of automation, potentially reducing demand for certain administrative or manual roles. However, new jobs may emerge in AI oversight, data ethics, and advanced analytics.
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What cities are hiring for Predictive Modeling jobs? Cities with the most Predictive Modeling job openings:
What are the most commonly searched types of Predictive Modeling jobs? The most popular types of Predictive Modeling jobs are:
What states have the most Predictive Modeling jobs? States with the most job openings for Predictive Modeling jobs include:
Senior Data Scientist, Predictive Modeling, Credit & Risk

Senior Data Scientist, Predictive Modeling, Credit & Risk

Carvana

Tempe, AZ • On-site

Other

Medical, Dental, Vision, Retirement

Posted 9 days ago


Carvana rating

6.8

Company rating: 6.8 out of 10

Based on 272 frontline employees who took The Breakroom Quiz

178th of 722 rated retailers


Job description

About Carvana...

At Carvana, we're changing the way people buy and sell cars. With an ambitious vision and a fundamentally different approach designed to be fun, fast, and fair, Carvana became the fastest-growing automotive retailer in history. We expanded nationally, went public on the New York Stock Exchange, sold our 1 millionth car, and reached the Fortune 500, all in just eight years.

Today, with 4 million retail customers and counting, Carvana is both the fastest-growing and the most profitable public automotive retailer, and we're just getting started. We continue to raise the bar for our customers as we tackle the enormous opportunity still ahead in the largest consumer vertical.

Working here means being part of a team that embraces change, celebrates creative problem solving, and always strives to be better. At Carvana, you'll have the opportunity to take on meaningful challenges, learn quickly, and help shape the future of automotive retail. If you're driven to grow and make an impact as part of a collaborative team, you'll fit right in. Learn more about what it's like to work here from the people that already do. 

Work Model: This is a 100% on-site role at our Tempe office, Monday through Friday.

About the Role

This role sits within Carvana's Credit & Risk modeling space, working on high-impact predictive models that inform risk assessment and decisioning across the business.

We are looking for a senior individual contributor who will help advance the technical capabilities of our core credit and risk models by developing, validating, and productionizing new modeling techniques and data signals.

Success in this role comes from steady, compounding improvement-introducing new ideas pragmatically, proving value early, and iterating toward more sophisticated approaches over time. While the work will focus on flagship credit and risk models, successful techniques and signals are expected to scale outward to other models and teams through shared workflows and modeling infrastructure.

This role is well suited for someone who operates comfortably at the intersection of advanced modeling and real-world delivery to balance tradeoffs between complexity and business objectives.

What You'll Be Doing

  • Improve core credit and risk models through a sequence of incremental advancements in accuracy, robustness, and coverage over time.
  • Leverage a wide range of structured and unstructured data sources across multiple modalities to drive sustained improvements in model accuracy and decision quality.
  • Design, train, and deploy advanced machine learning models, including (but not limited to) gradient boosting, representation learning, embeddings, and transformer-based approaches.
  • Use high-impact models as a testing ground for new techniques and data modalities, validating which ideas deliver measurable lift in production.
  • Build and apply rigorous evaluation frameworks (offline validation, backtests, simulations, online experiments) to guide iteration and decision-making.
  • Exercise strong judgment about model complexity and tradeoffs, balancing sophistication with reliability and maintainability.
  • Partner closely with data engineering and platform teams to ensure models are production-ready, scalable, monitorable, and maintainable.
  • Translate successful work into reusable patterns, abstractions, or signals that can be adopted across other modeling efforts.
  • Serve as a technical leader within the Predictive Modeling organization through design reviews, code reviews, and informal mentorship.

What You Should Have

  • 5-8+ years of experience building and deploying predictive models in production environments.
  • A demonstrated track record of delivering models and improving them iteratively over time, not just developing them offline.
  • Strong experience with modern machine learning techniques (e.g., LightGBM/XGBoost, neural networks, representation learning).
  • Excellent statistical intuition, including comfort reasoning about bias/variance tradeoffs, generalization, and experimental validity.
  • Fluency in Python and SQL, with production-quality coding standards.
  • Proven ability to take ambiguous, open-ended modeling problems from idea experiment production impact.
  • Bachelor's degree in Computer Science, Statistics, Math, Quantitative Economics, or similar field from an accredited undergraduate institution required.

If would also be great if you had

  • Hands-on experience with embeddings, transformers, or other deep representation models in real-world systems.
  • Experience integrating unstructured or semi-structured data (text, images, documents, device signals) into predictive models.
  • Familiarity with model monitoring, drift detection, and retraining strategies for high-impact decision systems.
  • Experience working in credit, risk, fraud, underwriting, or similar high-stakes modeling environments.

Notes on Experience

  • Research experience is a plus only if paired with a strong bias toward delivery and production impact.

What Success Looks Like

Over time, success in this role is reflected by:

  • Measurable improvements in the accuracy, robustness, or coverage of core credit and risk models.
  • New modeling techniques or data signals that transition from experimentation into sustained production use.
  • Clear patterns or abstractions that enable other teams to adopt and build on this work.
  • Strong alignment between modeling advances and real business outcomes.

What we'll offer in return

  • Full-Time Salary Position with a competitive salary.
  • Medical, Dental, and Vision benefits.
  • 401K with company match.
  • A multitude of perks including student loan payments, discounts on vehicles, benefits for your pets, and much more.
  • A great wellness program to keep you healthy and happy both physically and mentally.
  • Access to opportunities to expand your skill set and share your knowledge with others across the organization.
  • A company culture of promotions from within, with a start-up atmosphere allowing for varied and rapid career development.
  • A seat in one of the fastest-growing companies in the country.

Legal Stuff

Hiring is contingent on passing a complete background check. This role is eligible for visa sponsorship.

Carvana is an equal employment opportunity employer.  All applicants receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, marital status, national origin, age, mental or physical disability, protected veteran status, or genetic information, or any other basis protected by applicable law.  Carvana also prohibits harassment of applicants or employees based on any of these protected categories.

Please note this job description is not designed to contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice. 


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About Carvana

Sourced by ZipRecruiter

At Carvana, we sell cars, but we're not salespeople. Since 2013, we've been making it our mission to change the way people buy cars. We saw a huge problem with how much it can suck to buy a car the traditional way, so we committed ourselves to tackling one of the largest, yet-to-be-disrupted markets in the world - the $1T per year U.S. car market (yes, that's $Trillion with a "T").

Industry

Automobile dealers

Company size

5,001 - 10,000 Employees

Headquarters location

Tempe, AZ, US

Year founded

2011