We Do Consulting Differently
Preferred locations: New York, Chicago, Washington, D.C., Dallas, and Boston. Strong candidates in other locations may be considered case by case.
We do Consulting Differently
About the Practice
Berkeley Research Group is building a new Financial Institution Operations & Technology practice, with an initial focus on Commercial and Consumer Banking. We combine deep banking expertise, technology, and AI-enabled delivery to help financial institutions turn complex business challenges into measurable operational improvements.
Our delivery model centers on small, multidisciplinary pods that work closely with clients and take shared responsibility from discovery through implementation. Business analysts, pod leaders, technical architects, and engineers work against a prioritized backlog, bringing in domain, risk, design, and quality specialists as needed. This is an opportunity to help build a practice within an established consulting firm: delivering client results while developing reusable offerings, recruiting talent, and improving how we work.
The Role
We are considering candidates at the Managing Consultant and Senior Managing Consultant levels. You connect client objectives and operational realities with the requirements, data, and workflows engineers need to build effective solutions. You are equally comfortable leading a business workshop, mapping a process, and working through functional requirements with a technical team.
This is a senior, hands-on delivery role—not solely a strategy, documentation, or project-management position. You lead business and technology analysis for complex workstreams, stay engaged through development and testing, and help clients adopt the solution. You partner with the pod leader on priorities and outcomes and with the technical lead on feasibility and design; this role does not require you to be the pod’s primary software engineer or overall engagement lead.
What You’ll Do
Lead discovery with client stakeholders to clarify business problems, user needs, operational constraints, and opportunities for technology and AI-enabled improvement.
Assess current-state processes, systems, and data; design future-state workflows and operating-model changes that connect business objectives to practical implementation.
Translate findings into build-ready user stories, functional and nonfunctional requirements, business rules, process maps, and testable acceptance criteria.
Partner with technical architects and AI/data engineers to clarify business requirements, data and integration needs, assess feasibility and trade-offs, and resolve requirements during development.
Help the pod leader refine and sequence the backlog by business value, delivery dependencies, risk, and readiness; support sprint planning, demonstrations, and feedback-driven iteration.
Define success measures and baseline performance with clients; use data, stakeholder feedback, and clear executive communications to show progress and evaluate business impact.
Coordinate day-to-day workstream delivery, track actions and dependencies, and surface risks and decisions to the pod leader; support backlog refinement, sprint planning, demonstrations, and feedback-driven iteration.
Prepare and review client deliverables, analysis, and stakeholder updates; help establish performance baselines and track progress against agreed business outcomes.
Coordinate test scenarios, user acceptance testing, defect resolution, and evaluation of AI-enabled workflows, including controls and human review where appropriate.
Support implementation and adoption through business readiness, training, operating procedures, and handover; help ensure the delivered workflow remains usable after the engagement.
How You’ll Work in a Pod
Work directly with client business and technology teams and collaborate closely with pod colleagues. Own the quality and traceability of business analysis while contributing to the pod’s shared delivery outcomes.
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