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Remote Predictive Modeling Jobs (NOW HIRING)

SOSi

Data Scientist

OR · On-site +1

The contractor shall develop and refine predictive models, conduct exploratory data analysis, and ... Full remote flexibility. Working at SOSi All interested individuals will receive consideration and ...

Multi Media LLC

Machine Learning Engineer

$180K - $200K/yr

... predictive modeling, and AI-driven experimentation across a global-scale consumer platform. This is ... Fully Remote Optional * Health, Vision, Dental, and Life Insurance for you and any dependents, with ...

Natera

Sr. Scientist

San Carlos, CA, Austin, TX, or Remote, USA Sr. Scientist -CKD and rare disease Job Summary Natera ... Develop and implement robust predictive models to forecast clinical trends and outcomes using RWE ...

Natera

Sr. Scientist

OR · On-site +1

San Carlos, CA, Austin, TX, or Remote, USA Sr. Scientist -CKD and rare disease Job Summary Natera ... Predictive Analytics & Modeling: Develop and implement robust predictive models to forecast ...

Natera

Sr. Scientist

Boston, MA · On-site +1

San Carlos, CA, Austin, TX, or Remote, USA Sr. Scientist -CKD and rare disease Job Summary Natera ... Develop and implement robust predictive models to forecast clinical trends and outcomes using RWE ...

Marriott

Manager, Reporting and Analysis

Bethesda, MD · On-site +1

Familiarity with statistical methods, machine learning techniques, or predictive modeling ... Remote positions. Marriott International is the world's largest hotel company, with more brands ...

GD Resources LLC

Data Scientist - Remote Role

Remote Position Summary The Senior Data Scientist provides advanced analytical expertise supporting ... Develop fraud detection algorithms using statistical modeling and predictive analytics. * Perform ...

Humana, Inc.

Senior Informaticist

$89K - $109K/yr

Applying advanced statistical and predictive modeling techniques to develop, test, and validate ... Travel: While this is a remote position, occasional travel to Humana's offices for training or ...

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How much do remote predictive modeling jobs pay per hour?

As of Jul 12, 2026, the average hourly pay for remote predictive modeling in the United States is $59.65, according to ZipRecruiter salary data. Most workers in this role earn between $54.57 and $69.23 per hour, depending on experience, location, and employer.

What jobs will no longer exist in 2030?

Predictive modeling jobs are expected to evolve significantly by 2030, with some routine data analysis roles potentially automated through advanced AI and machine learning tools. However, roles requiring complex judgment, creativity, and domain expertise will continue to be essential, though the skills needed may shift toward managing and interpreting AI systems. Overall, jobs that rely heavily on manual, repetitive tasks are most at risk of disappearing or transforming.

Is 40 too late for data science?

Age is not a barrier to entering remote predictive modeling or data science roles. Many professionals successfully transition into data science later in their careers by acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications. Employers value experience and skills over age, making it possible to start or switch to data science at 40 or older.

Is predictive modeling difficult?

Predictive modeling as a job involves analyzing data, selecting appropriate algorithms, and validating models, which can be complex and requires strong analytical and programming skills. Success often depends on understanding statistical concepts, data preprocessing, and tools like Python or R, making it a challenging but manageable field for those with relevant training. Continuous learning and experience are key to mastering the skills needed for this role.

Can AI do predictive modeling?

AI is commonly used in predictive modeling to analyze data and forecast future outcomes. Predictive modeling involves techniques like machine learning algorithms, which are often implemented by data scientists and analysts using tools such as Python or R. These models are essential in various industries for decision-making and strategic planning.

What is the difference between Remote Predictive Modeling vs Remote Data Analysis?

AspectRemote Predictive ModelingRemote Data Analysis
Required SkillsStatistical modeling, machine learning, programming (Python, R)Data cleaning, descriptive statistics, visualization
Work EnvironmentCollaborative teams, project-based tasks, often in tech or financeData reporting, dashboard creation, business insights
Common CertificationsCertified Data Scientist, Machine Learning certificationsData Analysis certifications, Tableau or Power BI certifications

Remote Predictive Modeling focuses on building models to forecast future outcomes using advanced algorithms, while Remote Data Analysis involves examining existing data to generate insights and reports. Both roles require strong analytical skills, but predictive modeling emphasizes machine learning and statistical techniques, whereas data analysis centers on data interpretation and visualization.

More about Remote Predictive Modeling jobs
What cities are hiring for Remote Predictive Modeling jobs? Cities with the most Remote 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 Remote Predictive Modeling jobs? States with the most job openings for Remote Predictive Modeling jobs include:
What job categories do people searching Remote Predictive Modeling jobs look for? The top searched job categories for Remote Predictive Modeling jobs are:
Remote Predictive Modeling jobs near you
Data Scientist - Remote

Data Scientist - Remote

NAVA Software Solutions

Houston, TX • On-site, Remote

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

NAVA Software solutions is looking for a Data Scientist
Details:
Data Scientist
Location: Houston TX - Remote is ok
Duration: 12 months
Clients want a data scientist who can develop machine learning models to run forecast scenarios. Also, they want this person to be knowledgeable in AWS Cloud technology
A Data Scientist with physical pipeline experience typically specializes in analyzing and optimizing physical infrastructure pipelines, such as those used in the oil and gas industry or transportation networks. Here are some common job duties associated with this role:
  • Data collection and integration: Data scientists with physical pipeline experience gather data from various sources related to the infrastructure pipelines, such as sensors, SCADA (Supervisory Control and Data Acquisition) systems, or IoT devices. They integrate and consolidate the data for analysis and modeling.
  • Pipeline performance analysis: These professionals analyze the performance of physical pipelines by examining data related to flow rates, pressure levels, temperature, corrosion, and other relevant factors. They use statistical techniques and machine learning algorithms to identify patterns, anomalies, and potential issues that may affect pipeline operations.
  • Predictive modeling and maintenance optimization: Data scientists develop predictive models to forecast pipeline performance and detect potential failures or maintenance needs. They utilize historical data, sensor measurements, and other relevant parameters to train models that can predict future events, such as leaks, blockages, or equipment failures. By identifying critical maintenance requirements in advance, they can optimize maintenance schedules and minimize downtime.
  • Risk assessment and mitigation: Data scientists assess risks associated with physical pipelines, such as environmental hazards, security threats, or regulatory compliance. They develop risk assessment models and analyze the impact of different factors on pipeline safety and integrity. Based on these analyses, they propose mitigation strategies to minimize risks and ensure compliance with safety regulations.
  • Optimization of pipeline operations: Data scientists work on optimizing the operational efficiency of physical pipelines. They analyze data to identify areas of improvement, such as reducing energy consumption, optimizing transportation routes, or improving overall system performance. By applying data-driven approaches and algorithms, they provide recommendations to optimize pipeline operations and maximize efficiency.
  • Visualization and reporting: Data scientists with physical pipeline experience create visualizations, reports, and dashboards to communicate their findings and recommendations effectively. They present complex data in a visually understandable format, allowing stakeholders to make informed decisions regarding pipeline maintenance, operations, and risk management.
  • Collaboration with cross-functional teams: These professionals collaborate with engineers, domain experts, operations personnel, and other stakeholders involved in managing physical pipelines. They work together to understand the specific requirements, constraints, and challenges associated with the infrastructure. Effective communication and teamwork are essential to ensure alignment and successful implementation of data-driven solutions.
  • Continuous improvement and innovation: Data scientists keep up with the latest advancements in data science, machine learning, and pipeline technologies. They explore new methodologies, algorithms, and tools to enhance their skills and propose innovative solutions to address pipeline-related challenges.
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About NAVA Software Solutions

Sourced by ZipRecruiter

NAVA is a strategic partner for companies seeking to develop or customize software and products. Our team of experts leverages cutting-edge technology and deep industry knowledge to provide customized solutions that drive business success. Whether you're looking to improve your operations, increase efficiency, or bring a new product to market, NAVA has the expertise and resources to help you achieve your goals. Trust us to be your partner in software and product development.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Rocky Hill, CT, US

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