Utilities Business Analyst with AI/ML Experience

Duration :12+ Months Utilities Business Analyst with AI/ML experience We are seeking a highly analytical and tech-savvy Business Analyst to support our AI/ML initiatives for our client based in Arizona. The ideal candidate will bridge the gap between business stakeholders and data science teams, ensuring that machine learning solutions align with business goals and deliver measurable value. He/she will play a key role in defining project requirements, evaluating data readiness, and facilitating the successful deployment of AI/ML models. It will be great to find someone from Phoenix, AZ but even remote work is also fine. Required Qualifications: • Bachelor’s or Master’s degree in Business, Computer Science, Data Science, or a related field. • 14+ years of experience as a Business Analyst, with at least 4 years in AI/ML or data-driven projects. • 8+ years of experience in utility industry or related business areas. • Strong understanding of machine learning concepts, model lifecycle, and data pipelines. • Experience with tools like Azure DevOps (ADO), SQL, and data visualization platforms (e.g., Power BI). • Excellent communication, stakeholder management, and problem-solving skills. Preferred Qualifications: • Proven ability to lead large-scale business process initiatives • Experience working with cloud platforms (Azure, OCI) and ML Ops tools. • Experience working with Utilities • Familiarity with Python, R, or other data science languages (basic understanding is sufficient). • Certification in Business Analysis (CBAP, PMI-PBA) or AI/ML Key Responsibilities: • Collaborate with business stakeholders to identify opportunities for AI/ML applications. • Gather and translate business requirements into functional designs. • Conduct “As-Is” and “To-Be” process mapping, fit/gap analysis, and change impact assessments. • Conduct feasibility studies and impact assessments for proposed AI/ML solutions. • Develop and maintain business documentation including BRDs and functional specifications. • Define and track KPIs to measure the success of AI/ML models post-deployment. • Facilitate agile ceremonies (e.g., sprint planning, backlog grooming) for AI/ML projects. • Support model validation, A/B testing, and performance monitoring. • Document business processes, data flows, and model assumptions. • Communicate complex technical concepts to non-technical stakeholders. • Lead system, integration, and regression testing activities. • Ensure application controls meet audit and regulatory standards. • Facilitate communication between business units and technology providers. • Strong analytical mindset with attention to detail. Ability to work in cross-functional teams and manage multiple priorities