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Reliability Data Scientist Jobs (NOW HIRING)

Nissan Motor Co., Ltd.

Data Scientist

Smyrna, TN · On-site

The Data Scientist owns end-to-end execution-from problem framing and solution design to model ... reliability. * Build end-to-end analytical solutions using tools like Python, R, SQL, Power BI ...

ERC, Inc.

Data Scientist

Redstone Arsenal, AL · On-site

Use data science tools to improve data reliability, efficiency, and quality. * Responsible for planning tests to meet statistical requirements, developing Extract, Transform, Load (ETL) pipelines for ...

Kochava

Data Scientist

Sandpoint, ID · On-site

... reliability. • Actively contribute to model reviews, experimental design discussions, team planning, and post-deployment performance evaluations. • Work to find and address root causes of model ...

CYNET SYSTEMS

Data Scientist

Charlotte, NC · On-site

$60 - $65/hr

... reliability. * Utilize AWS analytics services (Athena, Redshift, QuickSight, EMR) for advanced ... Work with stakeholders to translate business objectives into data science solutions and actionable ...

SAIC

Data Scientist

Chantilly, VA · On-site +1

$200K - $240K/yr

Evaluates data quality, reliability, and efficiency throughout the data lifecycle. * Collaborating with other data scientists, software developers, operators, project managers, and clients to prepare ...

Kochava

Data Scientist

Sandpoint, ID · On-site

... reliability. • Actively contribute to model reviews, experimental design discussions, team planning, and post-deployment performance evaluations. • Work to find and address root causes of model ...

Great Gray

Data Scientist

The data scientist we seek comeswith strong experience in Python and its data science ecosystem ... and reliability in production. * Design, implement, and continuously improve LLM-powered ...

loomis

Data Scientist

Suwanee, GA

Summary The Data Scientist position is in the Logicpath division within Loomis. We are a team of ... support data confidence and forecast reliability. * Contribute to model documentation ...

Champions Funding LLC

Data Scientist

Gilbert, AZ · On-site

... reliability through continuous improvement. * Stay current with emerging technologies, AI ... Requirements: * Bachelor's degree required in Mathematics, Data Science, Computer Science ...

SAIC

Data Scientist

Chantilly, VA · On-site

... reliability, and efficiency throughout the data lifecycle. • Collaborating with other data scientists, software developers, operators, project managers, and clients to prepare data for predictive ...

Masterapp Labs

Data Scientist

Milton, GA · On-site

Data Scientist Location: Alpharetta, GA (Onsite) Interview: MS team interview/In-person Job Summary ... reliability in production environments. Key Responsibilities: * Design, develop, and deploy ML ...

New

loomis

Data Scientist

Suwanee, GA

Summary The position of Data Scientist is for the Logicpath division within Loomis. We are a team ... support data confidence and forecast reliability. * Contribute to model documentation ...

ERC Inc.

Data Scientist

Huntsville, AL · On-site

Use data science tools to improve data reliability, efficiency, and quality. Responsible for planning tests to meet statistical requirements, developing Extract, Transform, Load (ETL) pipelines for ...

loomis

Data Scientist

Suwanee, GA

Summary The position of Data Scientist is for the Logicpath division within Loomis. We are a team ... support data confidence and forecast reliability. * Contribute to model documentation ...

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Reliability Data Scientist information

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$37.5K

$122.7K

$196.5K

How much do reliability data scientist jobs pay per year?

As of Aug 6, 2026, the average yearly pay for reliability data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a reliability data scientist?

To thrive as a Reliability Data Scientist, you need a strong background in statistics, machine learning, data analysis, and reliability engineering, often supported by a degree in engineering, mathematics, or computer science. Familiarity with programming languages like Python or R, statistical analysis tools, and reliability modeling software such as Weibull++ is typically required. Strong problem-solving abilities, attention to detail, and clear communication skills help you translate complex data insights into actionable strategies for cross-functional teams. These skills are vital for accurately predicting system failures, optimizing maintenance, and driving improvements in product reliability and operational efficiency.

What is a reliability data scientist?

A Reliability Data Scientist is a professional who applies data science techniques to assess, predict, and improve the reliability and performance of systems, products, or processes. They analyze large datasets to identify failure patterns, root causes, and opportunities for preventive maintenance. By using statistical models and machine learning, Reliability Data Scientists help organizations reduce downtime, optimize maintenance schedules, and enhance overall operational efficiency.

How does a reliability data scientist typically collaborate with engineering and operations teams to improve system reliability?

A Reliability Data Scientist works closely with engineering and operations teams by analyzing large volumes of equipment and process data to identify potential failure patterns and root causes. They often participate in cross-functional meetings, share predictive models, and translate complex findings into actionable recommendations for maintenance schedules or design improvements. This collaboration ensures that technical insights are aligned with practical constraints and operational needs, ultimately enhancing system uptime and performance. Effective communication and a strong understanding of both data science and engineering principles are key to success in this collaborative environment.

What is the difference between Reliability Data Scientist vs Data Analyst?

AspectReliability Data ScientistData Analyst
Required CredentialsTypically requires a degree in data science, statistics, or engineering; certifications in reliability or data analysis are a plusUsually holds a degree in statistics, mathematics, or related field; certifications vary
Work EnvironmentWorks in industries like manufacturing, aerospace, or energy, focusing on reliability and predictive modelingWorks across various industries, analyzing data to support business decisions
Employer & Industry UsageUsed by engineering and maintenance teams to improve system reliabilityUsed by marketing, finance, and operations teams for insights and reporting

The Reliability Data Scientist specializes in analyzing data to predict and improve system reliability, often working closely with engineering teams. In contrast, Data Analysts focus on interpreting data to support business decisions across various sectors. While both roles require strong analytical skills, the Reliability Data Scientist emphasizes predictive modeling and reliability metrics.

More about Reliability Data Scientist jobs
What job categories do people searching Reliability Data Scientist jobs look for? The top searched job categories for Reliability Data Scientist jobs are:
Reliability Data Scientist jobs near you
Infographic showing various Reliability Data Scientist job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Data Scientist, Smart Maintenance, & Equipment Reliability

Patterson-UTI

Houston, TX • On-site

Full-time

Re-posted 8 days ago

Patterson-UTI rating

5.0

Company rating: 5.0 out of 10

Based on 23 frontline employees who took The Breakroom Quiz

80th of 86 rated oil and gas companies

Job description


As a Data Scientist for the Smart Maintenance initiative, you will support the creation of digital twins and predictive job models to reduce operational uncertainty and strengthen uptime during dynamic operations. You will help modernize maintenance and failure workflows to uncover subtle trends that traditional evaluations may miss, helping the company pursue a meaningful asset-life advantage. By moving data automatically across systems and removing reliance on manual reconciliation, you will help build a foundation for real-time maintenance management and total cost of ownership visibility. Your work will empower field teams with consolidated, purpose-built data that transforms every intervention into a precise, closed-loop maintenance event.
Key Responsibilities:
  • Support the development of predictive models and automated tracking tools to help maintenance teams shift from reactive to proactive workflows.

  • Assist in the integration of equipment telemetry and various data streams into modeling frameworks to improve lifecycle management.

  • Help build and test internal AI-driven tools and trend models to streamline technical troubleshooting and root cause analysis.

  • Contribute to the development of cost-visibility models to track equipment spend and total cost of ownership at different fleet levels.

  • Assist in the rationalization and optimization of equipment alarm systems to improve alert quality and reduce operational noise.

  • Monitor the impact of system alerts to help transition toward actionable, condition-based maintenance strategies.

  • Support data integrity efforts by helping to link information across disparate internal systems and work order platforms.

  • Collaborate on the design of user-friendly interfaces and digital aids that provide field personnel with accurate equipment history and procedures.

Job Requirements:
  • Prior experience in equipment reliability, predictive maintenance or physics-based modeling in oil and gas

  • Expert programming skills in Python (SciPy, NumPy) for simulation and model development

  • Strong foundation in reliability engineering methods such as root cause analysis (RCA), alarm management KPIs, and failure mode modeling.

  • Strong communication skills with the ability to explain complex models to non-technical stakeholders

  • Ability to manage multiple priorities and deliver results on time

Minimum Qualifications:
  • Bachelor's degree in Mechanical Engineering, Petroleum Engineering, Data Science or related field

  • 0-5 years of experience applying data science modeling or reliability engineering in industrial settings

  • 2+ years building and deploying data-science algorithms on cloud platforms (AWS, GCP or Azure)

  • A basic understanding of maintenance workflows, work orders, and asset hierarchies is required.

Preferred Qualifications:
  • Prior internship or project experience involving industrial IoT sensor data and predictive maintenance is preferred.

  • Master's degree or higher in a quantitative engineering or physical science discipline

  • Research publications or patents in equipment reliability, preventative maintenance or related areas

About Us
The Evolving Oil Field Demands Evolving Service Providers
NexTier is a leading provider of integrated completions that employs sustainable practices and equipment to support our customers' ESG goals while accelerating production in the most demanding US land basins.
Patterson-UTI is committed to a workplace free from discrimination and harassment, offering equal employment opportunities to all individuals regardless of personal characteristics protected by law. Employees are encouraged to report any concerns through multiple channels.

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