Client Solutions Analyst

FactualIQ builds next-generation Decision Engine workflows that integrate machine learning, agentic automation, and advanced reasoning tools into enterprise products that empower organizations to make better upside decisions faster.
About the Role
As a Client Solutions Analyst, you will serve as a critical bridge between FactualIQ’s clients and technical teams, with a primary focus on decision intelligence. You are responsible for understanding and modeling client decision-making processes, defining requirements and success criteria, and ensuring that delivered AI solutions measurably improve decision speed, quality, and confidence. Your work plays a central role in translating business decision flows into clearly defined, testable, and explainable AI-enabled solutions.
This is an analytical and client-facing role where you’ll work directly alongside Product Managers, AI/ML engineers, and practice leaders to support FactualIQ’s client solutions delivery. You’ll build expertise in enterprise decision modeling and AI solution delivery as FactualIQ scales its client engagements and solution portfolio.
What You'll Do
Decision Discovery & Analysis
Drive decision discovery by working with clients to document decision processes, constraints, inputs, and objectives.
Identify and document opportunities where AI can meaningfully improve decision quality, speed, and confidence.
Conduct data discovery across structured and unstructured sources, assessing data quality, availability, and suitability for AI and RAG-based solutions.
Define current- and target-state workflows, success metrics, and prioritization criteria.

Requirements & Solution Support
Translate decision needs into clear functional requirements, user stories, and acceptance criteria for both proof-of-concepts and production customizations, maintaining traceability from decision requirements to delivered capabilities.
Support solution validation through proof-of-concepts, QA, and user acceptance testing.
Track success metrics through delivery and early adoption, providing structured analysis of solution performance against defined criteria.
Serve as a client-facing partner during elicitation, development, and delivery, providing clear updates, managing expectations, and supporting refinements based on feedback.
Collaborate closely with data scientists, AI/ML engineers, platform engineers, and practice leaders to coordinate delivery and ensure solutions align with requirements and expected business impact.
Capture and document solution patterns, decision models, and lessons learned to build FactualIQ’s reusable knowledge base for future engagements.
Contribute to the development of client-facing deliverables including requirements documents, workflow analyses, and solution validation reports.
Support post-deployment review and adoption tracking to ensure solutions achieve sustained client value.

What You'll Bring
Bachelor’s degree in Business, Information Systems, Data Analytics, or a related field (or equivalent practical experience).
3+ years of experience in business analysis, consulting, process improvement, or client-facing delivery roles, with demonstrated experience supporting engagements from discovery through delivery.
Strong experience documenting and improving complex business or decision processes, including current-state analysis, gap identification, and target-state definition.
Working knowledge of data analytics concepts, AI/ML fundamentals, and modern decision-support workflows, including familiarity with how AI components integrate into enterprise decision-making systems.
Ability to translate business and decision needs into clear, actionable requirements, user stories, and acceptance criteria.
Experience working directly with external clients in enterprise environments, with awareness of complex stakeholder structures and governance requirements.
Experience supporting delivery coordination including timeline tracking, cross-functional alignment, and stakeholder communication.
Experience working in agile or structured delivery environments, including participation in sprint planning, backlog management, and iterative development cycles.
Excellent written and verbal communication skills, with the ability to engage effectively with business leaders, technical teams, and client stakeholders.

What You Might Bring
Background in management consulting, technology implementation, or analytics-driven organizations.
Hands-on experience with data tools such as Excel, SQL, Tableau, or similar, with understanding of core database concepts and data quality assessment.
Exposure to AI-enabled workflows such as retrieval-augmented generation (RAG), advanced analytics, or de