Principal Engineer, Operational Intelligence

Job not on LinkedIn

🕒 October 26

🏄 California, Florida, +3 more states – Remote

🏄 California – Remote 🐊 Florida – Remote ⚜️ Louisiana – Remote 🗽 New York – Remote 🦀 Maryland – Remote

⏰ Full Time

🔴 Lead

🧑‍💻 Full-stack Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 10%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.Why this score:

• Open for 17 days.
• Jobs at this company usually fill in 21 days.
• No salary listed.

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ASR Group

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

🍽️ Food & Beverage

🏭 Manufacturing

🌾 Agriculture

Food & Beverage • Manufacturing • Agriculture

ASR Group is a leading producer of sugar and sweeteners, known for its brand Florida Crystals. With a rich history in the agricultural sector, ASR Group specializes in the production and marketing of sugar derived from cane and beets, serving customers across North America and beyond. The company is committed to sustainable agricultural practices and offers various products that cater to both the food and beverage industries.

📋 Description

• Provide enterprise leadership and capability ownership for the Operational Intelligence discipline across refinery sites • Develop and maintain the Operational Intelligence strategy, standards, technology roadmap, architecture, and governance model • Own the enterprise Operational Context Standard, including asset models, measurement vocabulary, semantic classification, engineering units, naming conventions, and metadata quality expectations • Establish and chair the Operational Intelligence governance forum • Lead, coach, and develop the central team and build a sustainable talent pipeline • Partner with refinery and functional leaders to identify and prioritize high-value operational problems • Translate operational needs into a governed portfolio of intelligence initiatives with objectives, ownership, value measures, and adoption plans • Lead development, deployment, and sustainment of performance analytics, predictive capabilities, optimization opportunities, decision-support tools, and operational performance models • Define and own the production lifecycle for deployed intelligence solutions, including monitoring, drift detection, failure response, and retirement • Own the evaluation standard for analytical and AI outputs, including held-out validation, published accuracy, error, and fault rates • Establish the enterprise position on analytics compute location, operational data movement, and third-party or cloud AI services • Own build-versus-buy standards and technical recommendations for Operational Intelligence platforms and tools; evaluate vendors and manage supplier relationships • Build working relationships across Operations, Engineering, Maintenance, Reliability, EIC, Controls, Infrastructure, Cybersecurity, Information Technology, Finance, and other functions • Ensure analytics and AI initiatives follow approved data, security, architecture, lifecycle, validation, documentation, and governance expectations • Establish methods to measure operational and financial value, with Finance-verified post-implementation benefits • Guide responsible use of artificial intelligence within Operational Intelligence • Lead the Operational Intelligence Community of Practice • Provide technical and business guidance for data quality, operational context, model performance, solution sustainment, and adoption • Communicate portfolio performance, risks, decisions, business value, and roadmap progress to senior leadership and refinery stakeholders • Travel to manufacturing sites, vendor facilities, and project locations as required

🎯 Requirements

• Progressive leadership experience in industrial analytics, data science, process intelligence, operational technology, manufacturing technology, process optimization, engineering, or a related discipline • Demonstrated experience leading or mentoring data scientists, analytics professionals, engineers, or cross-functional technical teams • Experience converting manufacturing or operational problems into analytic use cases and measurable business outcomes • Experience developing, deploying, validating, and sustaining predictive analytics, optimization, decision-support, or AI-enabled solutions in a production operating environment • Experience with industrial time-series data at scale, including process historians and operational data infrastructure such as PI or AVEVA, MQTT and Sparkplug, or equivalent • Experience with ISA-95 or Unified Namespace style asset modeling • Experience defining data and context requirements and holding platform owners accountable to them • Experience combining statistical methods with first-principles process understanding, including mass and energy balance, thermodynamics, and reaction or crystallization behavior is strongly preferred • Experience working with operational data and partnering with Operations, Engineering, Maintenance, Reliability, Controls, and Information Technology teams • Experience establishing standards, roadmaps, governance, reusable methods, and a prioritized portfolio of analytics initiatives • Experience in refinery, milling, commodity processing, industrial chemical processing, food manufacturing, or another continuous or batch process environment is preferred • Bachelor’s degree in Engineering, Data Science, Computer Science, Statistics, Applied Mathematics, Industrial Engineering, Chemical Engineering, or a related technical field from an accredited university • Preferred Master’s degree or equivalent advanced experience is desirable • Strong knowledge of industrial analytics, statistical methods, predictive modeling, optimization, artificial intelligence, and decision-support practices • Ability to understand manufacturing processes, operational constraints, data context, and practical deployment requirements • Willingness and ability to travel across manufacturing sites and other business locations as required

🏖️ Benefits

• Equal opportunity employer • Travel across manufacturing sites and other business locations as required

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