Industrial Data Scientist

Value Driven Solutions, Inc.; Los Angeles (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Value Driven Solutions, Inc. seeks an Industrial Data Scientist to transform raw machine telemetry into predictive maintenance and process insights for factory self-correction.

You will clean and model time-series data from sensors, PLCs, historians and MES, build maintenance and quality models, and deploy them to edge or cloud with operator dashboards.

Qualifications

• 4+ years in data science with industrial/manufacturing data experience.
• Proficient in Python, SQL (pandas, scikit-learn, PyTorch or TensorFlow).
• Experience with time-series and sensor data (vibration, temperature, current).
• Familiarity with historians such as AVEVA PI or Canary.

Responsibilities

• Clean, contextualize and model time-series data from sensors, PLCs, historians and MES.
• Build predictive maintenance, anomaly detection and remaining-useful-life models.
• Develop multi-sensor correlation models for quality and yield.
• Deploy models to edge or cloud and build operator-facing dashboards.
• Walk plant engineers through results on the floor and refine models with their input.

Skills

Data science experience

Industrial data experience

Time-series data knowledge

Sensor data familiarity

Education

Bachelor’s degree or higher in a related field

Tools

Python

SQL

AVEVA PI

Canary

Job description

Industrial Data Scientist

Turn raw machine telemetry into predictive maintenance and process insights that help the factory self-correct.

What you'll do

• Clean, contextualize and model time-series data from sensors, PLCs, historians and MES
• Build predictive maintenance, anomaly detection and remaining-useful-life models
• Develop multi-sensor correlation models for quality and yield
• Deploy models to edge or cloud and build operator-facing dashboards
• Walk plant engineers through results on the floor and refine models with their input

Requirements

• 4+ years in data science, with industrial or manufacturing data experience
• Python (pandas, scikit-learn, PyTorch or TensorFlow) and SQL
• Experience with time-series and signal data (vibration, temperature, current)
• Familiarity with historians such as AVEVA PI or Canary

Nice to have: Databricks, Azure/AWS ML services, MLOps, reliability engineering knowledge, Power BI or Grafana.