TRC’s client, a leading EV battery manufacturer backed by major industry partners, is seeking an IT Director of Data & AI to lead data strategy, AI adoption, and digital transformation across the enterprise. This is a high-impact leadership role with significant growth opportunities.
Key Responsibilities:
Data Architecture & Ecosystem – Design secure, scalable architectures enabling real-time analytics, integration, and data flow across the organization.
AI Strategy & Solutions – Define enterprise AI strategy and deliver AI/ML solutions that improve manufacturing (predictive maintenance, quality assurance, process optimization, yield improvement).
Integration & Governance – Connect diverse data sources (IoT sensors, manufacturing equipment, SAP ERP, supply chain platforms) while ensuring data quality, privacy, and compliance (ISO, GDPR).
Technology Leadership – Evaluate and implement emerging AI, IoT, big data, and cloud technologies (AWS, Azure, GCP). Establish AI governance frameworks and best practices for MLOps.
Collaboration & Leadership – Partner with IT, engineering, and operations teams to translate business needs into scalable AI-powered solutions. Mentor data scientists, engineers, and analysts to foster innovation.
Qualifications:
Bachelor’s in CS, Data Science, Engineering, or related field; Master’s preferred.
10+ years in IT, with 7+ in data architecture, data engineering, or AI solution development (manufacturing/industrial experience preferred).
Expertise in SQL/NoSQL, ETL, and AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn).
Experience with big data platforms (Databricks, Spark, Hadoop) and IoT/time-series data.
Strong cloud expertise (AWS, Azure, GCP) and programming skills (Python, Java, or Scala).
Proven success implementing AI-driven solutions for process optimization or predictive maintenance.
Excellent communication and leadership skills; able to influence technical and non-technical stakeholders.
Preferred Skills:
EV, automotive, or battery manufacturing background.
Knowledge of materials science data, battery chemistry, or electrochemical modeling.
Experience with digital twins, simulation platforms, and CI/CD pipelines for AI/ML models.
Certifications in cloud architecture, data engineering, or machine learning.
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