Data and AI Engineer

The Brattle Group, Inc.; Boston (MA); On-site; USD 105,000 - 115,000; Full time

Benefits offered by this job

Competitive benefits package

Base salary bonus program

Job summary

The Brattle Group, Inc. is seeking a data engineer to join the Data & AI Engineering team in Boston to deliver hands-on data engineering, applied analytics, and AI-enabled workflows in client delivery and R&D.

You will build reproducible workflows using Python, SQL, notebooks, and version control, while testing assumptions and documenting how work was performed. Collaborate with consultants and economists to produce high-quality insights.

Qualifications

• Bachelor’s degree in Computer Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, Economics or related field.
• 0–3 years of data engineering, analytics or related technical work experience.
• Strong Python for data analysis and scripting experience.
• Experience with SQL and relational concepts.

Responsibilities

• Prepare, inspect, clean, reconstruct, and validate data from various formats.
• Build reproducible workflows using Python, SQL, notebooks, and version control.
• Test assumptions, troubleshoot issues, and document methods.
• Surface data limitations, quality issues, and blockers early.
• Support applied analytics, ML, and AI-enabled workflows.

Skills

Python

SQL

pandas

NumPy

scikit-learn

Git

Azure

Data cleaning

Education

Bachelor’s degree in a technical field

Tools

Git

Jupyter notebooks

Job description

Join The Brattle Group’s Data & AI Engineering team to deliver hands-on data engineering, applied analytics, and AI-enabled workflows in client delivery and applied R&D.

Responsibilities

• Prepare, inspect, clean, reconstruct, and validate data from structured datasets plus documents, reports, exports, PDFs, scans, and other formats not originally created for analysis
• Build reproducible workflows using Python, SQL, notebooks, and version control
• Test assumptions, troubleshoot issues, and document how work was performed
• Surface data limitations, quality issues, assumptions, blockers, and open questions early
• Support applied analytics, machine learning, and AI-enabled workflows where they improve outcomes
• Contribute to workflows such as text extraction, classification, summarization, embeddings, retrieval-augmented generation, model evaluation, automation, visualization, and rapid prototyping
• Use AI tools thoughtfully to accelerate learning and execution while maintaining responsibility for accuracy, confidentiality, defensibility, and quality
• Support applied R&D by prototyping, testing, and evaluating new tools, methods, and workflows before broader adoption
• Communicate progress, technical findings, assumptions, limitations, and trade-offs clearly to consultants, economists, technical peers, and other stakeholders
• Participate in code review, collaborative problem solving, documentation, and iterative refinement of work products
• Turn project lessons and R&D outputs into reusable team assets including examples, templates, documentation, and training materials

Requirements

• Bachelor’s degree in Computer Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, Economics with strong technical coursework, or a related field
• Equivalent hands-on technical experience, internships, research work, or project-based experience may be considered
• 0-3 years of professional experience in data engineering, analytics, applied AI, machine learning, software development, research, or related technical work
• Demonstrated interest in using AI tools, machine learning, or automation for practical problem solving, including willingness to learn responsible evaluation
• Comfort working in ambiguous problem spaces where tasks may need clarification, decomposition, and revision as new information emerges
• Strong foundation in Python for data analysis, scripting, automation, or prototyping, with exposure to pandas, NumPy, scikit-learn, or comparable tools
• Working knowledge of SQL and relational concepts including joins, aggregation, filtering, and practical data exploration
• Foundational understanding of statistics, data analysis, machine learning, or experimental evaluation, with interest in strengthening applied judgment over time
• Exposure to generative AI workflows such as prompt design, embeddings, vector search, retrieval-augmented generation, summarization, classification, or model evaluation
• Ability to work with structured, semi-structured, and unstructured data, including text-heavy documents and heterogeneous data sources
• Familiarity with software development practices including Git, notebooks, code review, documentation, testing, and reproducible workflows
• Familiarity with Azure or comparable cloud environments is helpful but not required
• Ability to learn new tools quickly and use AI-assisted development responsibly without assuming generated output is automatically correct
• Strong written and verbal communication skills to explain technical work, assumptions, limitations, and next steps
• Ability to manage multiple parallel workstreams in a fast-paced environment
• Flexible mindset to adapt to changing project priorities and client needs

Technologies

• Python, SQL, notebooks, version control
• pandas, NumPy, scikit-learn
• Git
• Embeddings, retrieval-augmented generation, vector search
• Prompt design, summarization, classification, model evaluation
• Azure

Salary and Location

• Location: Boston, MA (onsite)
• Salary: USD 105,000 - 115,000 per year

Benefits

• Competitive benefits package
• Base salary and bonus program for eligible roles based on individual and firm performance
• Anticipated base gross salary range for Boston, MA: $105,000 - $115,000 annually
• Actual salary depends on factors including experience and training

Team and Role Context

• The Data & AI Engineering team is embedded within Brattle’s consulting staff and supports client work while serving as an applied R&D function
• Work includes researching emerging technologies, prototyping analytical and AI-enabled workflows, and translating useful methods into reusable capabilities
• Engineers partner with economists, consultants, industry experts, and internal stakeholders across project delivery, reusable tools, documentation, training, and knowledge-sharing
• Engineers work under guidance from experienced technical leads including Senior Data & AI Engineers, Solutions Architects, and Research Engineers
• As experience grows, the role can progress toward deeper execution ownership, increased responsibility for solution design, advanced AI and research work, or a combination

Nature of the Work

• Technical path is often unclear, data is imperfect, and constraints are real
• Some workflows may be restricted or confidential, affecting how data is accessed, handled, or shared
• Multiple valid approaches may exist with trade-offs, with limited ability to return for clarification
• 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
• Team environment is academic, collegial, grounded, and highly collaborative

Candidate Expectations

• Not expected to own full workstreams on day one
• Expected to learn quickly, take initiative, and stretch beyond a narrow technical lane