Basic 5+ years as a Business Systems Analyst, explicitly focused on internal enterprise applications, corporate IT projects, or business process automation Experience with how core business systems (ERP, CRM) interconnect and exchange data via APIs Experience translating internal stakeholder requests into detailed user stories, process flow charts, and clear acceptance criteria Experience in Data Analysis, Data Science or AI and engineering Preferred Experience building assistants, agents, copilots, or AI products that use tools to complete tasks Strong point of view on when an agent should act autonomously, when it should ask for permission, and how to keep users in control Certification in Lean Six Sigma, Agile and Product Management Excellent written and verbal communication skills, with the ability to create clarity and alignment across senior cross-functional stakeholders
You are a developing recognized Specialist within your immediate team or function. You proactively use your expertise to anticipate challenges, improve how work gets done, and support others in delivering high-quality results. Design, build, and configure intelligent internal applications, and embedded AI tools. Workflow Automation, AI must trigger background actions without making the user click multiple buttons. Optimize complex business processes by bridging technical execution and leveraging internal data for measurable outcomes. Partner with cross-functional business units (Sales and Partnership) to diagnose operational bottlenecks. This position is an individual contributor role reporting to the Sr. Director, Sales & Partnerships Product Management. Responsibility Leverage growing functional and business knowledge to inform work and anticipate challenges Apply deepening functional expertise and upcoming technologies (like AI) to deliver both routine and non-routine work with increasing autonomy Anticipate common challenges in your area and use experience to recommend better approaches or solutions Connect domain expertise to business context, helping others understand how work supports functional and company goals Deliver end-to-end application product features independently, prioritizing based on business context, and driving outcomes at the program and team level Own increasingly complex or larger-scope deliverables within Sales and Partnership function, ensuring quality and reliability Contribute as a core member on application products, influencing approach within your area of expertise. Serve as a go-to resource or informal mentor proactively sharing knowledge through documentation, coaching or reviews Prioritize work based on business context, adapt plans to shifting needs, and keep execution on track across workstreams Select and optimize technical tools, potential AI solutions to improve productivity and solve complex problems, fostering a culture of learning Drive outcomes at the program and team level, influencing execution across workstreams Think beyond existing approaches, anticipate potential blockers, and bring fresh perspectives to solve moderately complex problems with support Think beyond existing approaches and established precedents Anticipate potential blockers and proactively seek input from more experienced colleagues Help bring fresh perspectives to solve moderately complex problems Support others in navigating ambiguity and encourage solution-focused thinking Apply a conceptual understanding of AI or ML and systems thinking to orchestrate AI microservices across core enterprise platforms, leveraging proficiency in data reasoning and context engineering to guide intelligent analysis and agile delivery Understand conceptually supervised or unsupervised learning, Large Language Models (LLMs), RAG architecture, and embeddings (Deep coding is not required, but architectural understanding is essential) Query and analyze data using SQL, and interpret statistical outputs, probabilities, and confidence intervals Map how AI microservices interact with core enterprise legacy systems (ERPs, CRMs) via REST APIs Structure enterprise context and business rules to guide AI-assisted analysis and pilot testing Utilize iterative lifecycle frameworks adapted for data science (e.g., CRISP-DM integrated with Agile or Scrum)