Senior Data Scientist — Manufacturing Operations

Experis Technology Group; Austin (TX); On-site; USD 124,000 - 138,000; Full time

Job summary

Experis Technology Group is seeking a Senior Data Scientist — Manufacturing Operations for a client in Austin, TX. You will analyze factory and industrial data to identify process anomalies and predict issues, and collaborate with production teams to optimize operations.

The role emphasizes building ML models, feature engineering from sensor data, and communicating actionable insights to stakeholders in a dynamic manufacturing environment.

Qualifications

• 8-10+ years of applied experience in data science within operational or industrial environments.
• Proficiency in Python and SQL with demonstrated experience working with large, complex datasets.
• Strong background in building and defending models such as classification, regression, clustering, anomaly detection, or time series analysis.
• Experience creating features from sensor, machine, quality, or operational data in manufacturing or similar sectors.
• Ability to quickly learn unfamiliar plant processes and communicate technical insights effectively.

Responsibilities

• Analyze factory and industrial data to identify process anomalies and predict potential issues before they occur.
• Build and validate statistical and machine learning models for process monitoring, quality prediction, and equipment health assessment.
• Collaborate with manufacturing, quality, maintenance, and data engineering teams to develop actionable insights.
• Clean, explore, and join fragmented operational datasets, transforming messy signals into meaningful features.
• Communicate findings clearly to stakeholders, providing explanations, thresholds, and recommended actions based on model outputs.

Skills

Python

SQL

Statistical modeling

Machine learning

Time series

Anomaly detection

Job description

Our client, a leader in manufacturing and industrial operations, is seeking a Senior Data Scientist — Manufacturing Operations to join their team. As a Senior Data Scientist — Manufacturing Operations, you will be part of the manufacturing support group, collaborating with teams focused on production lines, product quality, and system data management.

Job Title: Senior Data Scientist — Manufacturing Operations

Location: Austin, TX

Pay Range: $90 - $100 per hour

What's the Job?

• Analyze factory and industrial data to identify process anomalies and predict potential issues before they occur.
• Build and validate statistical and machine learning models for process monitoring, quality prediction, and equipment health assessment.
• Collaborate with manufacturing, quality, maintenance, and data engineering teams to develop actionable insights.
• Clean, explore, and join fragmented operational datasets, transforming messy signals into meaningful features.
• Communicate findings clearly to stakeholders, providing explanations, thresholds, and recommended actions based on model outputs.

What's Needed?

• 8-10+ years of applied experience in data science, analysis, and modeling within operational or industrial environments.
• Proficiency in Python and SQL, with demonstrated experience working with large, complex datasets.
• Strong background in building and defending models such as classification, regression, clustering, anomaly detection, or time series analysis.
• Experience creating features from sensor, machine, quality, or operational data, especially in manufacturing or similar sectors.
• Ability to quickly learn unfamiliar plant processes and communicate technical insights effectively.

What's in it for me?

• Opportunity to work on building a new AI-driven system from the ground up in a dynamic manufacturing environment.
• Engagement with cutting-edge data modeling and analytics techniques applied to real-world industrial challenges.
• Collaborative team environment with dedicated professionals in manufacturing and data science.
• Potential for contract extension beyond initial 5 months based on project needs and performance.
• Chance to make a tangible impact on manufacturing processes and operational efficiency.