Job description
Join us and contribute to driving excellence at MOTOLITE!
Job Summary
The Business Analyst is responsible for translating business requirements into data, analytics, AI, and automation solutions. The role supports the design and implementation of dashboards, data models, machine learning use cases, generative AI applications, and agentic AI workflows by defining requirements, validating outputs, and ensuring alignment between business objectives, data availability, and technical delivery.
Principal Duties: Gather, analyze, and document technical and functional requirements for data analytics, business intelligence, machine learning, generative AI, agentic AI, automation, and digital solution development. Translate business problems into data and AI solution specifications, including data sources, data flows, system logic, user workflows, output requirements, validation rules, and success metrics.
Develop business requirement documents, functional specifications, user stories, process maps, data dictionaries, dashboard wireframes, AI use case definitions, and acceptance criteria. Conduct data discovery and source system analysis to assess data availability, data quality, data granularity, refresh frequency, integration requirements, and transformation logic.
Coordinate with data engineers, BI developers, data scientists, AI engineers, application developers, IT, and business users throughout solution design, development, testing, deployment, and enhancement. Support the development of dashboards, reports, scorecards, monitoring systems, analytics applications, data products, AI assistants, and AI-enabled workflows by clarifying requirements and validating outputs.
Define and validate KPIs, business rules, calculation logic, data models, semantic layers, metric definitions, reporting dimensions, user roles, and access requirements. Support machine learning and advanced analytics development by defining target variables, input features, training data requirements, model output format, evaluation metrics, validation approach, and business interpretation.
Support generative AI and agentic AI development by defining knowledge sources, retrieval requirements, prompt logic, agent workflows, tool usage, response validation criteria, citation requirements, guardrails, and human-in-the-loop review points. Perform functional testing, data validation, user acceptance testing, regression checks, and output verification to ensure dashboards, analytics models, AI responses, and developed applications meet approved requirements.
Prepare and maintain technical documentation, including requirements traceability, data lineage, solution logic, test cases, release notes, user guides, training materials, and change request documentation. Monitor deployed Data and AI solutions for user adoption, data accuracy, performance issues, enhancement opportunities, and compliance with data governance, information security, access control, and responsible AI policies.
JOB SPECIFICATIONS Formal Education: Graduate of Information Technology, Computer Science, Data Science, Statistics, Mathematics, Industrial Engineering, Business Analytics, Engineering, or other related fields. Experience: With 3 to 5 years of relevant experience in business analysis, data analytics, business intelligence, dashboard development, data-driven process improvement, AI use case development, or digital solution development.
Experience in requirements gathering, stakeholder coordination, process analysis, data validation, dashboard testing, analytics project implementation, or AI-enabled solution development is an advantage. Training/Skills: Skilled in business requirements analysis, technical requirement documentation, process mapping, user story development, acceptance criteria definition, and functional specification preparation.
Proficient in data analytics and business intelligence tools such as Power BI, Tableau, SQL, Excel , or similar platforms, including dashboard validation and report logic review. Knowledgeable in data modeling concepts, KPI definition, metric calculation logic, semantic layers, data mapping, data profiling, data quality checks, and data governance fundamentals.
Familiar with database concepts, relational data structures, APIs, system integration, data pipelines, ETL/ELT processes, and analytics solution deployment. Familiar with machine learning concepts, including feature definition, target variable identification, model inputs and outputs, performance metrics, validation criteria, and business interpretation of model results.
Familiar with generative AI and agentic AI concepts, including prompt design, retrieval-augmented generation, knowledge bases, AI assistants, tool-calling workflows, citations, guardrails, and human-in-the-loop validation. Knowledgeable in SDLC, Agile methodology, backlog management, sprint planning, change requests, test case preparation, UAT, regression testing, and release documentation.
Skilled in technical documentation, stakeholder coordination, solution walkthroughs, issue tracking, user training, and presentation of data and AI solution requirements. "Motolite offers you not just a job, but a career with boundless opportunities"