Business Analyst - AI Solutions

About the role

This role analyzes business challenges and converts them into AI and automation solutions. The position bridges business stakeholders and technical teams to design, prototype, and adopt digital solutions.

Analysts turn data into clear answers. They pull numbers, clean data, build dashboards, and explain what changed and why. The work supports decisions across sales, product, marketing, and operations. Strong analysts pair technical skill with business curiosity. Analysts are the bridge between data and decisions. Most analysts own recurring reports and are expected to improve them over time.

Key facts

What you'll do

Stakeholders gather requirements, and these requirements are documented for business and solution design.

Processes are analyzed to identify improvements, and opportunities are defined to apply AI, automation, and digital transformation.

Business needs are translated into proof of concepts using approved tools, platforms, and low-code or no-code solutions.

Prototypes are built, and proposed solutions are validated with business teams to confirm fit.

Processes are evaluated alongside technical and business stakeholders, and innovative solutions are recommended.

Digital solutions are supported to enhance operational efficiency, and adoption is driven across the organization.

Workshops and discussions are facilitated to clarify requirements and align on objectives.

Requirements, workflows, designs, and proof-of-concept outcomes are documented for review and implementation.

Solution effectiveness is monitored, and enhancements are recommended based on performance.

Continuous improvement initiatives are driven in partnership with cross-functional teams.

Requirements

The posting states a bachelor's degree requirement. Experience as a Business Analyst in requirements gathering, business process analysis, and process improvement is necessary.

Hands-on experience with Python, TypeScript, or Angular is required.

Experience developing AI or automation proof of concepts and prototypes is required.

Hands-on experience with AppSheet or similar low-code or no-code platforms is required.

The ability to translate business requirements into functional solutions and working prototypes is required.

Strong analytical, problem-solving, and stakeholder management skills are mandatory.

Excellent verbal and written communication skills are required to present technical concepts to non-technical audiences.

Experience documenting requirements, workflows, business processes, and solution outcomes is required.

The ability to work effectively in a collaborative, cross-functional environment is required.

Experience with AI tools and platforms is highly desirable.

Experience with Google Workspace, Gemini, Skywise (Palantir Foundry), or similar digital and analytics platforms is a strong plus.

Practical notes

aerospace programs and export-controlled environments.

Typical interview steps

Analyst interviews often include a SQL or spreadsheet exercise, a case question, and behavioral rounds. Candidates may be asked to analyze a dataset, define a metric, or estimate an outcome. Presenting findings clearly is tested as often as the analysis itself. Interviewers often test speed and clarity with a timed exercise. Explaining what the numbers mean, not just what they are, is the differentiator.

Good to know

The role focuses on transforming business problems into AI and automation solutions.

The position involves using low-code and no-code platforms alongside AI tools.

Prototypes are developed, tested, and refined with business stakeholders.

The work supports digital transformation across industries such as aerospace, medical devices, robotics, and automotive.

Collaboration occurs within a large, cross-functional, global engineering environment.

Career growth

Analyst careers can grow into senior analyst, analytics manager, or data science roles. Some analysts move into product or business operations. Deeper technical skills or broader business ownership are the two main paths. Analyst roles are a common on-ramp into product, marketing, or operations leadership. Building deep domain knowledge alongside analytics is the fastest path.