Senior Business Analyst; AI COE
Verfasst am 2026-07-18
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Wirtschaft
Business Analyst, Wirtschaftsinformatik
The AI Senior Business Analyst is the domain partner who pairs directly with a Forward Deployed Engineer to automate the work of the business. You will embed in one or two functional areas at a time — learning how the work actually gets done, mapping the workflows and pain points, and turning that understanding into a steady stream of well‑scoped solutions for your FDE to build.
You are the primary feeder of work to the FDE: the person who builds AI solutions and ensures it solves a real problem the right way. In the early phases you will go deep in your first area and establish the standard operating rhythm;
Later, you will take on additional areas, mentor newer Business Analysts, and codify how this model scales across the enterprise.
At Lineage, the aim is not to build the largest technology team; instead, we are creating a small, highly skilled group that focuses on having the right mix of talents, skills, and the capacity to learn in areas that define our core differentiation. We leverage cloud services, best‑of‑breed libraries and components, and external teams to augment our capabilities with sufficient capacity.
This means that in addition to being a firsthand technologist, you also need to be able to take a project from an ambiguous business need to a production‑grade solution, and to collaborate with internal and external partners to deliver.
As a company, Lineage builds state‑of‑the‑art systems to make our employees productive, to meet and exceed our customers’ expectations, to assist in our growth, and to create a technology platform that enables Lineage to achieve its vision of transforming the food supply chain. This is one of the most impactful roles in that journey, and it will require someone who has a true passion for solving real business problems with the responsible application of AI, and for raising the bar for the engineers who follow.
PrimaryResponsibilities
Embed in one or more assigned business functions and build deep working knowledge of their processes, systems, data, and pain points — becoming the CoE’s resident expert on how those areas actually operate and where AI can automate or augment the work.
Partner with functional areas to document their current‑state processes — mapping how work flows today, where the handoffs, delays, and manual steps live — and use that map to identify the highest‑value ways to streamline and automate the work with AI.
Act as the primary feeder of work to your paired Forward Deployed Engineer — partnering with functional leaders and subject‑matter experts to translate the pain points you uncover into a prioritized, continuously refreshed backlog of well‑scoped solution briefs ready to build.
Develop business cases for the opportunities within your areas — including ROI estimates, effort sizing, and risk assessments — to support investment decisions.
Work side by side with your FDE throughout delivery — providing domain context, documenting requirements, facilitating user acceptance testing with the business, and driving adoption once solutions ship.
Create and maintain reporting for CoE leadership that quantifies the value your pod has delivered within its areas and the health of the backlog ahead.
Collaborate with the CoE to coordinate multi‑engagement timelines, resource allocation, and stakeholder communications.
Conduct post‑deployment impact analyses to validate projected ROI and surface the next wave of opportunities within your areas.
As the team scales, take on additional functional areas, mentor junior Business Analysts, and codify the repeatable BA–FDE pod playbook for embedding in a new area and standing up its backlog.
8+ years of experience in business analysis, management consulting, strategy operations, or a similar analytical role.
Experience working cross‑functionally with both technical teams and senior business stakeholders.
Proficiency with data analysis tools.
Domain experience in Lineage’s core functional areas or industry vertical preferred.
Familiarity with AI/ML concepts — enough to assess feasibility and have productive conversations with engineers, not necessarily to build models preferred.
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