Head of Commercial

About the role

This position is responsible for defining and executing the commercial strategy for a specialized data platform that serves the mining and critical minerals sector. The role owner will lead go-to-market initiatives, forge strategic partnerships, and manage commercial operations to accelerate discovery and informed resource decisions. Success in this position will be measured by the ability to translate complex data capabilities into clear value propositions for exploration and extraction organizations. The hire will work closely with product, engineering, and delivery teams to ensure commercial offerings are aligned with technical execution and customer needs. This leader will navigate emerging markets and complex external relationships to drive sustainable growth and adoption. The role requires a high level of commercial judgment to manage stakeholders and advance exploration strategies. Ultimately, the position focuses on building a strong portfolio of commercial initiatives that demonstrate tangible business impact in a data-driven industry.

Key facts

What you'll do

Own the end-to-end commercial strategy for a data platform that supports decision-making in the mining and critical minerals industry.

Define and lead go-to-market initiatives that position the platform as a critical tool for exploration and resource evaluation.

Develop and manage strategic partnerships with organizations that rely on data-driven decisions in technical sectors.

Build and refine commercial operations to support evolving exploration workflows and resource discovery processes.

Engage with complex external relationships to identify new opportunities and expand market presence in emerging segments.

Align product and partnership teams with commercial priorities to ensure cohesive execution and customer value.

Communicate clearly with both technical and executive stakeholders to build confidence and secure buy-in for initiatives.

Navigate evolving environments where exploration strategies and resource assessments are continuously advancing.

Use structured processes and data platforms to support cross-functional collaboration and external engagements.

Leverage experience in mining, energy, and industrial technology sectors to inform commercial decisions and market entry.

Employ strong commercial judgment to manage stakeholders and succeed in markets with evolving regulations and standards.

Integrate machine learning methods and probabilistic modeling insights into commercial discussions and value propositions.

Ensure clarity and confidence in stakeholder management across technical, operational, and executive audiences.

Support the adoption of data platforms that enhance geoscience workflows and resource decision-making.

Drive the development of metrics and analyses that demonstrate the business impact of commercial activities.

Requirements

The posting states a bachelor's degree requirement.

Experience leading complex commercial engagements is required within evolving environments.

Experience in strategic partnerships or market-facing initiatives is essential for success in this role.

Experience within mining, energy, natural resources, industrial technology, or similarly technical industries that rely on data-driven decision making is required.

Complex external relationships must be managed with strong commercial judgment and professionalism.

Processes must be built and operations conducted comfortably in evolving environments as exploration and resource strategies advance.

Clarity and confidence are required in stakeholder management and communication across technical and executive audiences.

Partnership and product teams must be aligned while navigating emerging markets and evolving commercial priorities.

A recognized degree is a standard qualification for the role and must be presented as part of the eligibility criteria.

Nice to have

Experience in the mining, critical minerals, or resource technology sectors is preferred.

A track record of successful partnerships and commercial strategy execution is valued.

Skills & tools

General experience with data platforms, geoscience workflows, and resource sector tools supports this role.

Clear communication and structured processes enable collaboration across cross-functional teams and external partners.

Machine learning methods and probabilistic modeling are common in similar positions.

Practical notes

The role is based in the Redwood City Office and operates as a full_time position.

Terra AI is an equal opportunity employer.

Typical interview steps

Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.

Good to know

Work in this role involves data platforms used for geoscience and resource evaluation.

Tools commonly include machine learning and probabilistic modeling methods.

Collaboration with cross-functional teams and external partners is a regular part of the work.

This role focuses on commercial strategy and stakeholder engagement in a fast-growing company.

Questions to ask

Good questions to ask the employer in the interview: what does success look like in the first six months, how is the team structured, what is the current biggest challenge, and how are decisions made. Asking about growth paths and the review process is also well received. Employers expect questions, and good ones show preparation.

Career growth

Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.