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Dow Chemical Company

Manufactures high-performance materials across industries

IT Leader, Data Science

Data ScienceConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A bachelor's degree, relevant military experience at the E5 rank or Petty Officer 2nd Class or higher, or 12 years of experience in lieu of a bachelor's degree is required.
  • A minimum of three years of people management experience is required, including direct responsibility for coaching, performance management, development planning, and team outcomes.
  • Demonstrated experience leading complex, cross-functional initiatives involving business and technology stakeholders is required.
  • The ability to work legally in the United States is required.
  • Experience managing high-skill technical, analytical, digital, or scientific teams is preferred; direct leadership of data scientists or advanced analytics professionals is preferred.
  • Working knowledge of data science solution lifecycles, software engineering, MLOps, model governance, product delivery, and associated risks is preferred.
  • Experience managing a portfolio of data science, analytics, AI, or digital initiatives, including prioritization, governance, resource planning, risk management, and value tracking is preferred.
  • The ability to build effective teams, represent technical capabilities to business leaders, and translate ambiguous challenges into actionable work is preferred.
  • Strong consulting, facilitation, and communication skills, with success influencing across a large, complex enterprise and leading through ambiguity, are preferred.
  • Commitment to continuous learning, talent development, inclusion, and improvement is preferred.
  • The role requires understanding data science teams' work, lifecycle, risks, and support needs; developing talent; setting expectations; giving constructive feedback; building trust; holding teams accountable; representing team capacity and trade-offs; balancing priorities, resources, risks, dependencies, value, sustainability, and stakeholder expectations; and establishing governance, accountability, and measures that improve quality, predictability, transparency, and results.

Responsibilities

  • Lead, coach, and develop a team of data scientists through clear expectations, feedback, career guidance, and accountability for results.
  • Create a safe, inclusive, and high-performing environment that supports learning, innovation, constructive challenge, and continuous improvement.
  • Remove organizational barriers and support workforce planning, hiring, onboarding, recognition, succession, and capability development.
  • Build trusted partnerships with business and functional leaders to identify, frame, and prioritize data science opportunities with clear outcomes, success measures, and ownership.
  • Maintain awareness of relevant data science and emerging AI capabilities and help stakeholders assess where they can create responsible, sustainable value.
  • Represent the team with technical and non-technical audiences, communicating capabilities, capacity, priorities, trade-offs, risks, and contributions.
  • Own and prioritize the team's portfolio, balancing enterprise needs, business value, capacity, dependencies, development needs, and delivery risk.
  • Establish disciplined practices for intake, planning, governance, status reporting, risk management, and executive communication across the data science lifecycle.
  • Ensure initiatives have clear objectives, ownership, stakeholder engagement, measurable outcomes, delivery plans, and decision points.
  • Lead portfolio reviews and adjust priorities or resources as business needs and delivery conditions change.
  • Partner with senior practitioners and adjacent technology teams to set direction, clarify responsibilities, remove barriers, strengthen reusable practices, and address material technical risk.
  • Set expectations for fit-for-purpose documentation, governance, model validation, production readiness, monitoring, support, and retirement.
  • Ensure the team has the standards, tools, expertise, and partnerships needed to apply modern data science, software engineering, and MLOps practices.
  • Use meaningful measures and stakeholder feedback to improve delivery, adoption, team effectiveness, operating discipline, and business value.

About the Company

Dow Chemical Company

Manufactures high-performance materials across industries

Dow Inc. is a materials science company that develops high-performance materials for a range of industries, including agriculture, construction, and healthcare. Its products include agricultural films, construction materials, and medical packaging, all created through advanced science and technology to meet specific customer needs. These materials help customers improve product quality, efficiency, and sustainability. Dow differentiates itself through a broad, cross-industry portfolio, its focus on transparent and substantiated environmental and social claims, and industry recognition such as the 2024 BIG Innovation Awards. The company's goal is to advance innovation and sustainability by delivering reliable, high-quality materials that support customers across various markets.

Company size
10,001+
Company stage
IPO
Headquarters
Midland, MI
Founded
1897

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