Inactive
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SI Group

Global performance additives and APIs supplier

Director Artificial Intelligence

Applied Machine LearningPosted on Oct 16
Full-timeThe Woodlands, TX, USANo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree in data science, computer science, statistics, or engineering, or equivalent experience.
  • At least 10 years of experience in data science and artificial intelligence.
  • At least 5 years of team or program management experience.
  • Experience with Python, SQL, modern machine learning frameworks, and cloud machine learning platforms.

Responsibilities

  • Lead the development and execution of the company's responsible artificial intelligence strategy, partnering with functional leaders to identify needs and opportunities, build a strategic roadmap, and deliver solutions for employee productivity and manufacturing operations.
  • Establish and oversee the company's artificial intelligence governance framework, ensuring alignment with security and regulatory requirements and measuring business value from artificial intelligence and automation initiatives.
  • Contribute directly to the design, development, and deployment of artificial intelligence models and agents while supporting organization-wide training, adoption, and artificial intelligence fluency.
  • Set a multi-year artificial intelligence strategy tied to enterprise growth priorities, present it to the executive leadership team, and keep it current as technology and markets change.
  • Own artificial intelligence policy, risk assessment, and model oversight, including privacy, intellectual property, cybersecurity, and validated manufacturing environments.
  • Partner with Master Data, Enterprise Applications, Infrastructure, Cybersecurity, and Operational Technology teams to enable artificial intelligence use of data from enterprise resource planning, customer relationship management, manufacturing execution systems, plant historians, and laboratory systems.
  • Define reference architecture and standards for models, agents, and integrations, including the boundary between information technology and operational technology.
  • Recruit, develop, and lead a small, senior team, and hold partners and service providers accountable for clear outcomes.
  • Own the artificial intelligence budget, platform spending, and vendor contracts.
  • Partner with business leaders to transform business processes around artificial intelligence rather than adding tools to existing processes.
  • Lead the company's Artificial Intelligence Transformation Office.
  • Own the roadmap, configuration, licensing, vendor relationships, and costs for each everyday artificial intelligence platform; decide which tools the company standardizes on and retires.
  • Build role-based training, a champions network, and a library of proven use cases for each function and region.
  • Enable business teams to build assistants and agents within the platforms, with clear standards for what they may connect to and automate.
  • Partner with Cybersecurity, Legal, and Data Governance on acceptable use, data classification, access controls, and prevention of unsanctioned artificial intelligence tools.
  • Track active usage, license utilization, time returned, and employee satisfaction, and report results to the executive team.
  • Run an ongoing intake of employee ideas and feedback and promote the strongest candidates into differentiating capabilities.
  • Identify, size, and rank opportunities with leaders in Manufacturing, Supply Chain, Commercial, Research and Development, and corporate functions; fund and advance opportunities that deliver return on investment.
  • Design, build, and deploy models and agents independently and with the team, from prototype to production at scale across sites.
  • Apply forecasting, optimization, anomaly detection, and predictive modeling to yield, quality, asset reliability, energy use, demand, and pricing.
  • Build agents that reason over company data and act inside core systems, targeting multi-step work in sales, supply chain, formulation, manufacturing, customer service, and regulatory documentation.
  • Establish machine learning operations and large language model operations practices for evaluation, monitoring, drift detection, human oversight, cost control, and safe rollback.
  • Set a baseline before each build, track benefits after go-live, and report earnings before interest, taxes, depreciation, and amortization impact rigorously for Finance and board review.
  • Choose the fastest responsible route for each use case and ensure the company owns the capability and know-how that create competitive advantage.

Desired Qualifications

  • Manufacturing experience.

About the Company

SI Group

Global performance additives and APIs supplier

SI Group supplies specialty chemical products and solutions, focusing on performance additives, process solutions, active pharmaceutical ingredients (APIs), and chemical intermediates. Its offerings enhance quality, performance, and durability across industries such as pharmaceuticals, automotive, and consumer goods. How it works: the company develops tailored chemical formulations and process solutions for customers, leveraging advanced materials and safety/compliance practices. It operates globally with facilities in nine countries and serves customers in over 80 countries, collaborating closely to meet specific application needs. Differences from competitors: emphasis on customer-centric, safety-compliant solutions delivered through global production networks and a broad portfolio across multiple market segments. Goal: to help customers improve product performance while maintaining safety and environmental responsibility through reliable, compliant chemical solutions.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
The Woodlands, TX
Founded
1999

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