Albert Invent

Albert Invent

Scientific Solutions Architect

Remote (United States)

Sponsorship not specified$30k-$50kDetected 17 days ago
PythonAWSMachine LearningSalesInventory ManagementLeadershipCommunicationCollaborationMentoringPublic SpeakingAdaptability

About the role

  • We are looking for an ambitious and results-driven Scientific Solutions Architect to join our growing team.
  • This role is critical to driving successful outcomes for Albert's most strategically important customers, from the fuzzy front end of a deployment through to realized value.

Responsibilities

  • Design and deliver complex, enterprise-grade scientific solutions that translate customer R&D workflows into Albert OS, ensuring measurable value at each stage of the customer journey.
  • Identify and develop high-impact use cases early in the deployment cycle, translating complex scientific requirements into clear, actionable delivery plans.
  • Business Case Analysis & Value Capture Collaborate with sales and technical teams to craft compelling business cases, quantifying outcomes tied to cost savings, process efficiency, innovation speed, and risk reduction.
  • Translate customer R&D needs and pain points into actionable technical solutions aligned to business goals, relaying and prioritizing requirements to internal teams to drive timely delivery.
  • Drive platform adoption by demonstrating measurable success in both pre-sales and post-implementation contexts.
  • Partner with R&D and non-R&D customer teams to implement and scale successful pilots and deployments, connecting value to business goals across project types including innovation, product development, product maintenance, and operational excellence.
  • Sales Support Support enterprise sales by delivering technical presentations, leading exploratory discussions, mapping laboratory workflows to Albert, and constructing architectural and data flow diagrams.
  • Develop presentation materials that emphasize the value of Albert's solutions to customer business needs, and manage key partnership discussions to help shape effective, scalable engagements.
  • Partner with Sales Enablement to provide input on customer engagement strategies that support successful, long-term solution implementation and value alignment.
  • Leadership & Impact Mentor and develop junior scientific staff, raising the team's capability in both scientific domain knowledge and customer-facing delivery.

Requirements

  • You will have Master's degree or higher in Chemistry, Chemical Engineering, Materials Science, Polymer Science, or a related scientific or engineering discipline.
  • Proven track record of operating independently in ambiguous, early-stage customer engagements where scope and priorities must be defined from the ground up.

Nice to have

  • Our platform helps R&D organizations achieve a structured data foundation, digitalize their formulation and testing processes, and empower scientists to innovate faster, smarter, and at scale.
  • You'll bridge the gap between scientific R&D workflows and enterprise digital strategy, acting as a trusted advisor who brings structure to ambiguous environments and champions the customer's long-term success.
  • If you're passionate about cutting-edge technology and thrive in a fast-paced, mission-driven environment, we want to hear from you.
  • Act as a trusted scientific advisor to customer executives and technical stakeholders, shaping digital transformation strategy and aligning Albert's capabilities to long-term business goals.
  • Represent Albert in strategic customer conversations and technical workshops, acting as the voice of the customer within Albert to help shape product offerings and service delivery.

Compensation

  • $30k-$50k

Company info

  • Comfortable operating in dynamic, evolving customer and company environments where priorities shift and playbooks are still being written.
  • Guide customers in mapping legacy tools and workflows into unified data workflows within Albert, including integrations with existing systems.

This listing is sourced directly from Albert Invent's careers page and normalized into a canonical job model.