Supports Factory of the Future and Industry 4.0 initiatives by leveraging data, analytics, and AI technologies to improve manufacturing efficiency, quality, and operational performance.
Compensation
$90,000 - $125,000 annual compensation
Responsibilities
Leads industry 4.0 and AI initiatives by identifying, prioritizing, and implementing data-driven solutions that optimize manufacturing processes across molding, assembly, and co‑extrusion processes.
Collaborates with cross‑functional teams including engineering, operations, IT, and automation teams to integrate digital technologies and analytics into production systems.
Develops and maintains data infrastructure including ETL pipelines, databases, SQL queries, and data environments to support manufacturing analytics and AI applications.
Collects, validates, and manages production data from multiple sources, including PLCs, HMIs, sensors, and enterprise systems, ensuring data accuracy and integrity.
Designs, develops, and optimizes machine learning and AI models to improve quality, productivity, predictive maintenance, process control, and operational efficiency.
Requirements
Bachelor's degree in Computer Science, Engineering, Data Science, or related discipline
This role sits at the intersection of SRE, DevOps, and data, helping to improve reliability, observability, and operational maturity of data platforms, Kubernetes-based deployment systems, internal applications, and cloud environments.
Compensation
In the U.S., the standard base pay range for this role is $102,800.00 - $190,204.00 Annual.
Responsibilities
Monitor service health, respond to alerts, and participate in incident response for cloud, Kubernetes, application, and data platform environments.
Support the reliability of internal applications, APIs, workers, streaming consumers, event-driven services, and deployment workflows used by data engineering and business teams.
Build and maintain dashboards, alerting, runbooks, and operational documentation that improve detection and recovery speed.
Improve observability for Databricks environments, including job health, Spark streaming workloads, structured streaming metrics, cluster behavior, failures, latency, throughput, and cost signals.
Senior Data Scientist who designs, develops, and implements machine learning models, AI systems, and statistical modeling to generate actionable insights for business problems and product development.
Compensation
Pay Range: $108,960.00 - $163,440.00 Annual
Responsibilities
Designs, develops, programs and implements Machine Learning Models (Clustering, Classification or Regressions models).
Performs Statistical Modelling and Measurements by applying data engineering, feature engineering, statistical methods, ML modelling and AI techniques.
Develops and applies novel models on customer data to identify areas to increase profits and reduce losses.
Partners with experimentalists to translate models into testable hypotheses.
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