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.
Skills Required
- 4+ years of experience in data science
- Experience working with industrial or manufacturing data
- Proficiency with Python, including pandas and scikit-learn
- Experience with PyTorch or TensorFlow
- SQL proficiency
- Experience with time-series and signal data, including vibration, temperature, or current data
- Familiarity with industrial historians such as AVEVA PI or Canary
- Experience with Databricks
- Experience with Azure or AWS machine learning services
- MLOps experience
- Reliability engineering knowledge
- Experience with Power BI or Grafana
What We Do
Value Driven Solutions (VDS) is an operational-excellence consulting firm serving middle-market companies, private-equity firms, and portfolio companies. It improves operational and financial performance through supply-chain optimization, operations, finance, technology, procurement, strategic consulting, and vetted interim executives. VDS also applies Lean Six Sigma, automation, robotics, AI, and analytics to strengthen efficiency, margins, capital efficiency, and enterprise value, with measurable, lasting results.
