Data and AI Engineer

The Brattle Group, a privately held, global economics consulting firm, is looking for a Data and AI Engineer to join our Boston, MA office.

The Data & AI Engineer is an early-career role within Brattle’s Data & AI Engineering team, focused on hands‑on technical work across client delivery, applied R&D, and internal capability‑building. This role is designed for candidates who are strong builders, fast learners, and clear communicators, and who want to develop technical judgment in a setting where problems are varied, ambiguous, and often time‑sensitive.

This is not a narrowly defined pipeline role or a heads‑down engineering track. Data & AI Engineers work across data engineering, applied analytics, machine learning, and AI‑enabled workflows, staying close to implementation while learning how technical choices affect real client work.

Candidates are not expected to arrive as experts across data engineering, solution architecture, and applied AI research. They are expected to be hands‑on, curious, coachable, and comfortable learning quickly.

The Data & AI Engineering team is a specialized technical group embedded within Brattle’s consulting staff. The team supports client work while also serving as an applied R&D function for the firm: researching emerging technologies, prototyping new analytical and AI‑enabled workflows, and translating useful methods into reusable capabilities.

The team partners with economists, consultants, industry experts, and internal stakeholders to improve how the firm works with data, analytics, machine learning, and AI through project delivery, reusable tools, documentation, training, and knowledge‑sharing.

Data & AI Engineers work under the guidance of more experienced technical leads, including Senior Data & AI Engineers, Solutions Architects, and Research Engineers. As experience grows, the role can develop toward deeper execution ownership, increased responsibility for solution design, more advanced AI and research work, or some combination of those paths.

Data & AI Engineers work on problems where the technical path is often unclear, the data is imperfect, and the constraints are real. Source materials may be incomplete, inconsistent, degraded through prior systems, or difficult to interpret. Some matters also involve restricted or confidential workflows that shape how data can be accessed, handled, or shared.

The role requires practical judgment. There may be multiple valid approaches, each with trade‑offs, and limited ability to go back to the source for clarification. Data & AI Engineers are expected to reason carefully from imperfect inputs, document assumptions, surface limitations, and help build solutions that are defensible, reproducible, timely, and fit for purpose.

Project timelines may shift quickly based on external events, negotiations, litigation deadlines, or client needs. Some work is recurring and operational; some is one‑off or exploratory. The right candidate is a resourceful, practical builder: someone who can stay organized, adapt to changing constraints, and make progress without losing rigor or composure.

The team environment is academic, collegial, grounded, and highly collaborative. We value curiosity, humility, initiative, clear communication, and practical intelligence. The work can be technically advanced, but the culture is not ego‑driven. We are looking for people who are resourceful, friendly, proactive, flexible, and able to work well with others in a global, connected consulting environment.

• Prepare, inspect, clean, reconstruct, and validate data from a wide range of sources, including structured datasets, documents, reports, exports, PDFs, scans, and other formats that may not have been created for analysis
• Use Python, SQL, notebooks, version control, and related tools to build reproducible workflows, test assumptions, troubleshoot issues, and document how work was performed
• Identify data limitations, quality issues, assumptions, blockers, and open questions early
• Support applied analytics, machine learning, and AI‑enabled workflows where they are useful to the…