Business Analyst – Data Analytics & AI Projects

Position: Business Analyst – Data Analytics & AI Projects Company: Confidential Location: Remote Employment Type: Contract Role Overview As a Consultant / Business Analyst on our Data Analytics and AI team, you will be the critical link between business challenges and data-driven solutions. Working across industries and functions, you’ll lead client discovery efforts, uncover high-impact analytics use cases, and translate complex business problems into structured data models and AI-driven solutions. This role requires strong stakeholder engagement, deep curiosity, and a passion for understanding both data and human behavior. You will collaborate closely with data engineers, product managers, and subject matter experts to bring insight-led change to life through scalable AI applications. Employee Value Proposition (EVP) Purpose: This role directly impacts how our clients unlock value from their data by aligning AI and analytics initiatives with pressing business needs. You will serve as the translator between business objectives and technical solutions, shaping the direction of innovation in high-stakes environments. Growth: As a core member of a cross-functional data transformation team, you will gain exposure to a variety of industries, AI applications, and emerging technologies. You will accelerate your development as a strategic thinker, customer advocate, and solution architect by owning critical engagements from discovery through delivery. Motivators: If you enjoy problem-solving, asking “why” until it becomes clear, and making data useful for real people, this role will keep you energized. It’s ideal for someone who wants to influence real change, lead complex conversations, and be recognized for connecting people, processes, and data into scalable value. Major Objectives (First-Year Key Performance Objectives) 1. Lead End-to-End Discovery and Business Context Mapping for Analytics/AI Projects Within the first 60 days, take ownership of client discovery efforts, including stakeholder interviews, user journey mapping, and business process analysis. Deliver a concise business context brief and opportunity map that defines at least three AI/analytics use cases prioritized by strategic impact. Success will be measured by client feedback, alignment with business KPIs, and clarity of documentation. 1. Translate Business Needs into Actionable Solution Requirements and Functional Specs By the end of month 4, complete the functional specification and solution scoping phase for a key client project, including use case definitions, data requirements, wireframes, and MVP scope. Collaborate with engineering, product, and client teams to finalize delivery timelines. Your work should enable a smooth handoff to delivery teams and be validated by stakeholder acceptance. 1. Support Change Management and Drive Adoption of AI/Analytics Solutions Over the first 6–12 months, take a lead role in preparing client-facing demos, training guides, and stakeholder communication plans. Partner with change champions to monitor adoption and support behavioral change. Success will be measured by adoption rates, stakeholder satisfaction, and completion of feedback loops for solution refinement. Critical Subtasks 1. Conduct Structured Stakeholder Interviews to Identify Business Pain Points During the first 30 days, lead interviews and workshops with key client stakeholders to surface hidden challenges, performance gaps, and priorities. Document findings clearly and synthesize themes into initial solution hypotheses. 1. Map End-to-End Business Processes and Key User Personas Within the first 6 weeks, document current and future-state process flows using tools like swimlanes or SIPOC diagrams. Define critical user personas and their interactions with the data ecosystem to inform solution design. 1. Perform Data Discovery and Business-Led Profiling with Engineering Partners By week 8, partner with data engineering to profile key datasets. Translate technical outputs into business-relevant insights, highlighting gaps, risks, and data quality issues. Document findings in a Data Discovery Summary aligned with business use cases. 1. Collaborate on MVP Scope Definition and Success Metrics with Product Team By the end of month 3, finalize MVP criteria, functional requirements, and success metrics for at least one AI or analytics use case. Contribute to the delivery roadmap, linking milestones to business outcomes. 1. Develop and Deliver Training & Adoption Materials for End Users Within 6 months, co-create and deliver training sessions, job aids, or quick reference guides to ensure adoption and value realization. Tailor messaging to user personas and track participation. 1. Contribute to ISMS and Information Security Best Practices Throughout the engagement, ensure compliance with information security policies. Assist the ISMS Manager with documentation, training, and audits as needed. Report issues proactively and reinforce a culture of data governance. 1. Continuously Evaluate and Integrate AI to Improve Performance Within the first 90–180 days, take ownership of identifying how AI and automation tools can support or enhance the core responsibilities of this role. Evaluate tasks that could be streamlined or improved, lead pilots, and embed continuous AI adoption into daily work. You’ll Be a Great Fit If You... • Have 3–7 years of experience in business analysis or consulting (ideally with data/AI exposure) • Thrive in client-facing roles and enjoy untangling complex problems • Think in systems — and know how to zoom from user need to data model • Have some exposure to AI/ML, Power BI/Tableau, or SQL, and want more • Get excited about career-defining work, not just incremental wins