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Remote Data Scientist Risk Jobs in Houston, TX (NOW HIRING)

Relativity

Senior Applied Scientist

Houston, TX · On-site +1

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Applied Science Team The Applied Science team operates at the core of Relativity's AI development.

Vitol

Software Engineer in Data Science

Houston, TX · On-site +1

$109.30K - $131.30K/yr

Translate: Act as a local champion for data science and AI, helping users adopt tools and ... technical debt and delivery risk * Collaborative approach to problem solving - ability to ...

Vitol

Software Engineer in Data Science

Houston, TX · On-site +1

$109.30K - $131.30K/yr

Translate: Act as a local champion for data science and AI, helping users adopt tools and ... technical debt and delivery risk * Collaborative approach to problem solving - ability to ...

Gainwell Technologies LLC

Principal Data Sciences

Houston, TX · On-site +1

$124K - $177.10K/yr

Summary As a(n) Principal Data Sciences at Gainwell, you can contribute your skills as we harness ... Fully Remote Opportunity - Work from anywhere in the U.S. * Minimal Travel Required - Occasional ...

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Relativity

Principal Applied Scientist

Houston, TX · On-site +1

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Applied Science Team The Applied Science team sits at the core of Relativity's AI development. We ...

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Remote Data Scientist Risk information

See Houston, TX salary details

$35.8K

$117.2K

$187.7K

How much do remote data scientist risk jobs pay per year?

As of May 29, 2026, the average yearly pay for remote data scientist risk in Houston, TX is $117,212.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,100.00 and $129,900.00 per year, depending on experience, location, and employer.
What are the most commonly searched types of Data Scientist Risk jobs in Houston, TX? The most popular types of Data Scientist Risk jobs in Houston, TX are:
What are popular job titles related to Remote Data Scientist Risk jobs in Houston, TX? For Remote Data Scientist Risk jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Remote Data Scientist Risk jobs in Houston, TX look for? The top searched job categories for Remote Data Scientist Risk jobs in Houston, TX are:
What cities near Houston, TX are hiring for Remote Data Scientist Risk jobs? Cities near Houston, TX with the most Remote Data Scientist Risk job openings:
Remote Data Scientist Risk jobs near you
Infographic showing various Remote Data Scientist Risk job openings in Houston, TX as of May 2026, with employment types broken down into 1% Internship, 2% As Needed, 81% Full Time, 7% Part Time, and 9% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $117,212 per year, or $56.4 per hour.
Data Scientist - Remote

Data Scientist - Remote

NAVA Software Solutions

Houston, TX • On-site, Remote

Full-time

Posted 25 days ago

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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