Data Scientist

Tenth Revolution Group; Dallas (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

Tenth Revolution Group in Dallas, Texas seeks a hands-on Manufacturing Data Scientist to develop and deploy machine learning solutions that improve equipment reliability, product quality, process performance, and operational efficiency.

You'll work with plant-floor data and stakeholders to turn complex sensor and MES data into actionable insights, moving projects from prototyping to production and driving measurable value.

Qualifications

• Bachelor's degree in a related field.
• 4+ years of experience in data science, ML, or advanced analytics.
• Strong Python and SQL skills.
• Experience with manufacturing, industrial, or time-series datasets.
• Production deployment experience and data validation.

Responsibilities

• Develop and deploy ML solutions in manufacturing environments.
• Build models for predictive maintenance, forecasting, process optimization, and quality improvement.
• Work with sensors, historians, MES, maintenance, and quality data sources.
• Engineer features and transform noisy production data into insights.
• Design scalable data science solutions from PoC to production.
• Collaborate with operations, engineering, maintenance, quality, and business stakeholders.
• Apply statistical methods and control techniques to reduce variation and increase uptime.
• Support AI initiatives including generative AI and advanced analytics.
• Communicate findings to technical and non-technical audiences.

Skills

Python

SQL

Data science

Machine learning

Statistical analysis

Production deployment

Time-series data

Education

Bachelor's degree in Data Science, Computer Science, Engineering, Mathematics or Statistics

Tools

MLflow

Docker

CI/CD

Databricks

OPC UA / OT tools

Job description

Locations: Dallas, TX | Frederick, MD | Joplin, MO | Phillipsburg, KS | Tuscaloosa, AL

My client is an industry-leading manufacturing organization that is investing heavily in AI, machine learning, advanced analytics, and digital transformation initiatives across its operations.

This is an opportunity for a hands-on Manufacturing Data Scientist to develop and deploy machine learning solutions that improve equipment reliability, product quality, process performance, and operational efficiency. You'll work directly with manufacturing stakeholders, leveraging plant-floor data to solve real-world business challenges while helping advance the organization's long-term vision for autonomous and data-driven manufacturing.

What You'll Be Doing

• Develop and deploy machine learning, predictive analytics, and anomaly detection solutions in manufacturing environments.
• Build models focused on predictive maintenance, forecasting, process optimization, equipment reliability, and quality improvement.
• Work with complex industrial datasets from sensors, historians, MES platforms, maintenance systems, quality systems, and other manufacturing data sources.
• Engineer features and transform noisy, real-world production data into actionable insights.
• Design and implement scalable data science solutions that move beyond proof of concept and into production.
• Partner with operations, engineering, maintenance, quality, and business stakeholders to identify opportunities and deliver measurable value.
• Apply statistical methods, process control techniques, and machine learning to reduce variation, improve process capability, and increase uptime.
• Support the development of next-generation AI initiatives, including generative AI, agentic workflows, and advanced analytics applications.
• Communicate findings and recommendations to both technical and non-technical audiences.

What We're Looking For

• Bachelor's degree in Data Science, Computer Science, Engineering, Mathematics, Statistics, or a related field.
• 4+ years of experience in Data Science, Machine Learning, Advanced Analytics, or related disciplines.
• Strong experience with Python and SQL.
• Experience developing machine learning models on operational, manufacturing, industrial, or time-series datasets.
• Hands-on experience working with imperfect data sources, including sensor data, machine-generated data, and manually entered operational data.
• Understanding of statistical analysis, anomaly detection, predictive modeling, and data validation techniques.
• Experience deploying and maintaining models in production environments.
• Strong problem-solving abilities and the ability to work independently in fast-paced environments.
• Excellent communication skills and the ability to translate technical findings into business impact.

Preferred Experience

• Manufacturing, industrial, process manufacturing, automotive, chemical, consumer products, building materials, food & beverage, or similar industry experience.
• Predictive maintenance, reliability analytics, condition monitoring, or equipment health monitoring.
• MLOps tools and practices including MLflow, Docker, CI/CD, or model monitoring.
• Cloud platforms such as Azure or Databricks.
• Experience with historian platforms, OPC UA, MQTT, MES, SCADA, or other operational technology (OT) systems.
• Exposure to Generative AI, RAG, LLMs, agent frameworks, or modern AI engineering practices.
• Six Sigma, Statistical Process Control (SPC), or continuous improvement methodologies.