Senior Data Scientist: AI & Analytics for Manufacturing

Systems Technology Group, Inc. (STG); Austin (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Systems Technology Group, Inc. (STG) seeks a Sr. Data Scientist in Austin, TX to lead advanced analytics initiatives for Fortune 500 clients.

You will build end-to-end data platforms, create predictive and prescriptive models, and deliver dashboards and interfaces that translate complex data into actionable business decisions.

The role emphasizes data quality, collaboration with data engineering and IT, and opportunities to apply AI across manufacturing and operations.

Qualifications

• 8–10 years of data modeling experience.
• 8–10 years of building data pipelines.
• 8–10 years of data analytics and handling messy data.
• Experience digging into data and building end-to-end systems from scratch.
• Interest in building AI applications.

Responsibilities

• Build reliable analytical datasets and pipelines using SQL, Python, Spark, and Databricks.
• Develop, validate, and monitor predictive or prescriptive models for manufacturing use cases such as downtime, defects, bottlenecks, and maintenance.
• Create dashboards, visualizations, reports, and user interfaces communicating trends and risks.
• Productionize analytics in partnership with data engineering, application, and Manufacturing IT teams.
• Support manufacturing modernization initiatives including cloud migration and data-product development.

Skills

Data modeling

Data pipelines

Data analytics

AI application

Creative thinking

Dashboards/visualization

Productionize analytics

Tools

SQL

Python

Spark

Databricks

Job description

Systems Technology Group, Inc. (STG) seeks a Sr. Data Scientist in Austin, TX to lead advanced analytics initiatives for Fortune 500 clients.

You will build end-to-end data platforms, create predictive and prescriptive models, and deliver dashboards and interfaces that translate complex data into actionable business decisions.

The role emphasizes data quality, collaboration with data engineering and IT, and opportunities to apply AI across manufacturing and operations.