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Industrial Data Scientist Jobs (NOW HIRING)

Sr Data Scientist (APM)

Atlanta, GA · On-site

$150 - $200/hr

Industrial Data Science for Predictive Maintenance and Asset Reliability * Failure Prediction, Remaining Useful Life Modeling, and Reliability Analytics * Equipment Health Monitoring, Anomaly ...

Industrial Data Science for Predictive Maintenance and Asset Reliability * Failure Prediction, Remaining Useful Life Modeling, and Reliability Analytics * Equipment Health Monitoring, Anomaly ...

$91K - $109K/yr

Responsibilities / Tasks The Industrial Data Engineer is responsible for designing, developing, and ... Bachelor's orMaster's Degree in Computer Science, Data Science, Engineering, or a related field.

Qualifications * 1. Bachelor's degree in Computer Science, Data Science, Engineering, or a related ... We are a growing manufacturing company looking to add a Industrial Data Analytics Engineer to our ...

We are seeking a highly skilled Senior Data Scientist with experience in bioprocess control to join ... Experience with industrial data systems and cloud platforms. * Knowledge of reinforcement learning ...

Job Summary : IFAB Corp is seeking a highly analytical and results-driven Data Scientist to ... and coating services for OEM and industrial customers. Founded in 1994, the company is ...

... Computer Science, Information Technology, or a related field; equivalent relevant industrial ... Historian calculations, data-quality management, derived tags, deadbanding, store-and-forward ...

Data Scientist

San Diego, CA · On-site

$125 - $150/hr

The AUKUS, Submarines, and Industrial Base Group (ASIG), within the Sea, Land, Air Division ... SPA is looking for a Mid-Level Data Scientist with Artificial Intelligence experience in the ...

The Data Scientist plays a critical role in advancing Vantage's analytics, automation, and data ... Experience working with large-scale operational, IoT, or industrial datasets strongly preferred.

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Industrial Data Scientist information

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$46K

$165K

$243.5K

How much do industrial data scientist jobs pay per year?

As of Sep 9, 2026, the average yearly pay for industrial data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is an industrial data scientist?

An Industrial Data Scientist is a professional who applies data science techniques to optimize processes, improve efficiency, and solve complex problems within industrial settings such as manufacturing, energy, or logistics. They analyze large datasets from industrial equipment, sensors, and operations to uncover insights that can drive business decisions. Their work often involves predictive maintenance, quality control, supply chain optimization, and automation. Industrial Data Scientists typically collaborate with engineers, IT specialists, and business leaders to implement data-driven solutions that enhance productivity and reduce costs.

How does an industrial data scientist typically collaborate with engineering and operations teams?

Industrial Data Scientists work closely with engineering and operations teams to identify key data sources, understand process workflows, and translate business needs into actionable analytics. They often participate in cross-functional meetings to discuss production challenges and jointly develop data-driven solutions, such as predictive maintenance models or process optimizations. Effective communication and a collaborative mindset are essential, as the role involves explaining complex data findings to non-technical stakeholders and ensuring that analytical solutions are practical and implementable on the plant floor.

What are the key skills and qualifications needed to thrive as an industrial data scientist, and why are they important?

To thrive as an Industrial Data Scientist, you need strong foundations in statistics, machine learning, and domain-specific knowledge, typically supported by a degree in data science, engineering, or a related field. Familiarity with programming languages like Python or R, industrial IoT systems, and data visualization tools such as Tableau or Power BI is often required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data into actionable insights for cross-functional teams. These skills ensure that data-driven decisions optimize industrial processes, improve efficiency, and provide a competitive edge.

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

AspectIndustrial Data ScientistData Analyst
Required CredentialsBachelor's or Master's in Data Science, Engineering, or related fields; often some industry-specific certificationsBachelor's degree in Data Analysis, Statistics, or related fields; certifications like Microsoft Excel or Tableau are common
Work EnvironmentIndustrial settings, manufacturing plants, supply chain environments, or energy sectorsOffice-based, business, finance, or marketing departments
Employer & Industry UsageManufacturing, energy, logistics, and industrial sectorsRetail, finance, healthcare, and corporate sectors

While both roles involve data analysis, Industrial Data Scientists focus on complex data modeling and predictive analytics specific to industrial processes, whereas Data Analysts primarily handle data reporting and visualization for business insights.

What are popular job titles related to Industrial Data Scientist jobs?

For Industrial Data Scientist jobs, the most frequently searched job titles are:

Infographic showing various Industrial Data Scientist job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 83% Full Time, 12% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Sr Data Scientist (APM)

Atlanta, GA

Full-time

Medical, Life

Re-posted 18 days ago


Job description

Position Overview

Novelis is one of the world leaders in aluminum recycling and rolling and a leading sustainable aluminum solutions provider. Driven by our purpose of shaping a sustainable world together, we work alongside our customers to provide innovative solutions to the aerospace, automotive, beverage packaging and specialty markets. Headquartered in Atlanta, Georgia, Novelis has approximately 13,000 employees in 32 operating facilities on 4 continents.

Responsibilities & Qualifications

The Senior Data Scientist, (APM), supports the design, development, and deployment of data science and machine learning solutions that improve asset reliability, reduce unplanned downtime, and strengthen maintenance decision-making across Novelis' manufacturing operations. Reporting to the Sr AI Engineer Leader of APM, this role partners with Operations, Reliability, Data Engineering, and AI Governance to translate industrial data into practical, actionable insights. The role develops and supports failure-prediction models, equipment health-monitoring logic, anomaly detection, and remaining-useful-life estimators for human decision support-not autonomous control.

This is a hands-on senior data science role with a reliability focus. The Senior Data Scientist helps convert prioritized APM use cases into reliable production solutions by combining statistical analysis, machine learning, time-series modeling, sensor data interpretation, and practical understanding of maintenance and reliability workflows. The role works within the technical direction, roadmap, and architecture established by the Sr AI Engineer Leader of APM while maintaining model quality, operational usability, and trust with plant stakeholders.

Capability Alignment

This role is aligned to the APM delivery team within the Decision Intelligence & AI Enablement pillar and contributes to the following enterprise capabilities:

  • Industrial Data Science for Predictive Maintenance and Asset Reliability
  • Failure Prediction, Remaining Useful Life Modeling, and Reliability Analytics
  • Equipment Health Monitoring, Anomaly Detection, and Alert Quality Improvement
  • Time-Series Modeling, Sensor Data Analysis, and Operational Context Interpretation
  • Model Lifecycle Management for Industrial Analytics and Production Data Science
  • Responsible AI Compliance in Operational Environments, aligned to AI Governance standards

Responsibilities

Data Science Development & Reliability Analytics

  • Develop and deliver data science components of predictive maintenance and asset-reliability systems, including data preparation, feature engineering, exploratory analysis, model development, deployment support, and monitoring workflows.
  • Build, validate, and improve production-grade failure prediction models, equipment health scores, remaining-useful-life estimators, and anomaly detection methods that produce useful recommendations for maintenance and operations teams.
  • Apply statistical analysis, machine learning, time-series modeling, and reliability engineering judgment to solve industrial monitoring problems using appropriate evaluation methods and deployment patterns.
  • Analyze sensor, historian, maintenance, and operational data to identify asset behavior, failure patterns, signal quality issues, model drift, and opportunities to improve alert precision and credibility.
  • Support model lifecycle management through monitoring, retraining support, documentation, version control, testing, validation, and production troubleshooting.

Execution Alignment & Cross-Functional Delivery

  • Deliver assigned APM work in alignment with Novelis' enterprise data and reliability priorities, including trusted data, operational reliability, metal flow optimization, sustainability goals, and operational efficiency.
  • Work with reliability, operations, automation, information technology, and data engineering stakeholders to connect analytical findings to practical maintenance decisions and sustainable production use.
  • Support feature scoping, sprint execution, testing, deployment, user adoption, and continuous improvement activities aligned to the APM delivery roadmap and critical metric framework.

Accountability Boundaries

This role delivers data science models, analyses, and engineering components within the roadmap, technical architecture, and technology direction owned by the Sr AI Engineer Leader of APM. It supports predictions and recommendations for maintenance and operations teams; people in Operations and Reliability make and complete the maintenance decisions and actions. This role contributes to the APM roadmap, model standards, analytics validation, production monitoring, and stakeholder feedback loops, but does not own enterprise architecture, autonomous closed-loop control, AI governance standards, core data platforms, business target definitions, data governance rules, master data policy, or data access configuration. Where a use case warrants autonomous closed-loop execution rather than human action, this role supports handoff to AI Automation for engineering and runtime ownership.

Minimum Qualifications

  • Bachelor's degree in Data Science, Computer Science, Engineering, Statistics, Applied Mathematics, Reliability Engineering, or a related field.
  • Minimum of 3 years of experience in data science, machine learning, reliability analytics, predictive maintenance, industrial analytics, or related applied analytics work.
  • Experience developing analytical or predictive models using time-series data, sensor data, equipment telemetry, maintenance records, or manufacturing process data.
  • Proficiency in Python, SQL, and common data science or machine learning libraries; ability to investigate data quality issues and explain model outputs to technical and non-technical stakeholders.
  • Strong analytical, communication, and problem-solving skills, with interest in manufacturing, maintenance, reliability, or industrial decision support.

Preferred Qualifications

  • Master's degree or advanced certification in Data Science, Machine Learning, Statistics, Engineering, Reliability, or a related field.
  • Experience in manufacturing, industrial operations, reliability engineering, maintenance analytics, or asset performance management.
  • Familiarity with industrial historians, condition monitoring data, edge or cloud analytics environments, Databricks, Power BI, Azure, or production model deployment practices.
  • Experience translating analytical outputs into maintenance, reliability, or operational actions in partnership with plant stakeholders.
  • Familiarity with production data science, model deployment, or analytics platform practices, including tools such as Docker, Kubernetes, Azure, Databricks, or similar cloud and containerized deployment environments.

Please note that we are unable to provide visa sponsorship for this position. Candidates must be legally authorized to work in the United States without the need for current or future sponsorship

What We Offer:

Novelis' benefits say a lot about how we care for each other. Our employees and their families have many different needs. As a result, our benefits offer choices on many levels and are high in quality, driven by the marketplace, and affordable. In addition to core benefits, we provide these unique to the industry benefits:

  • Family Growth Programs: Paid parental Leave, Adoption Assistance, Fertility Treatment, Childcare Discount and Nursing Mom Support
  • Employee Assistance Programs: free resources available 24/7 to you and your family in the areas of mental health, family life, and career and financial guidance
  • Wellness Programs: incentives for wellness activities, wellness spending account, programs for building healthy habits, virtual physical therapy for joint, back, and pelvic health, health management programs and more.
  • Diabetes Management Program
  • Pet insurance
  • Identity Theft Protection
  • PerkSpot Discount Program
  • Tuition assistance and career development programs!

#LI- AC1

#LI- Hybrid

Location Profile

Novelis' Global Corporate and North America Headquarters is located in the Buckhead neighborhood of Atlanta GA employing around 700 people. Supporting it's 31 operations worldwide Novelis' corporate office is home to the executive leadership team and global functions that support the automotive beverage can and high-end specialties value streams. The City of Atlanta provides a diverse and family-friendly place to live with countless museums cultural organizations and educational institutions including the Georgia Aquarium Woodruff Arts Center CNN Center Georgia Tech and Mercedes-Benz Stadium. In the Atlanta area Novelis has strong community partnerships with Atlanta Habitat for Humanity GeorgiaFIRST and Agape Youth and Family Center in addition to many local museums and community groups.

Novelis recognizes its talented and diverse workforce as a key competitive advantage. Novelis provides equal employment opportunities to all employees and applicants.All terms and conditions of employment at Novelis including recruiting hiring placement promotion termination layoffs recalls transfers leaves of absence compensation and training are without regard to race color religion age sex national origin disability status genetics protected veteran status sexual orientation gender identity or expression or any other characteristic protected by federal provincial or local laws.

Disclaimer

We encourage all potential candidates to follow the protocols below and to be diligent when sharing any personal information:1. Check the job posting is live and valid via our careers page: Careers - Novelis2. Verify any communication with us by contacting our talent team at Careers - Novelis

Employment Type: FULL_TIME