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Data and AI Engineer

Boston, Massachusetts, United States

Open 3 months, first seen by us 112 days ago
Pay
$91,000–115,000/year · Gross — pay source
Flexible mindset to adapt to changing project priorities and client needs Brattle offers a competitive benefits package, base salary, and bonus program for eligible roles based on individual and firm performance. The anticipated base gross salary range for this position in Boston, MA is $91,000 - $115,000 annually. Actual salary will depend on a variety of factors, including experience and training. This position is not eligible for immigration sponsorship.
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Work setting
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Employment
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Before you apply

New graduates
Open to new graduatesThe 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
Work authorization
Must already have the right to workThis position is not eligible for immigration sponsorship

What you’ll work on

Full posting
  • Clean, reconstruct, and validate data from spreadsheets, PDFs, scans, and other messy sources

  • Build reproducible workflows in Python and SQL and document how work was done

  • Support machine learning and AI workflows such as extraction, summarization, and retrieval-augmented generation

  • Prototype and evaluate new tools and methods before wider adoption

  • Flag data limitations, assumptions, and open questions early and explain trade-offs to consultants and economists

From the employer’s posting
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
Contribute to workflows involving text extraction, classification, summarization, embeddings, retrieval-augmented generation, model evaluation, automation, visualization, or rapid prototyping
Support applied R&D by helping prototype, test, and evaluate new tools, methods, and workflows before they are adopted more broadly
Identify data limitations, quality issues, assumptions, blockers, and open questions early
Education & alternatives
THE CANDIDATE - 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 also be considered
Apply at The Brattle Group

Posting record

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Open 3 monthsWe first saw this posting 112 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jul 15, 2026112 days ago
Recorded sightings
49
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

Lower than most similar jobs

$91K–$115K against $166K–$240K, the middle half of what similar US postings state.

From 1,279 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 112

Up longer than most. Similar jobs usually come down between day 6 and day 69.

From 4,381 similar postings that came down. Coming down is not always a hire.

The Brattle Group is hiring

1 open job

  • No new data jobs since July
  • Its jobs tend to stay up a long time
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • Azure
  • NumPy
  • pandas
  • scikit-learn
Where the posting names them
- 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
- Comfort working in ambiguous problem spaces where the task may need to be clarified, decomposed, and revised as new information emerges - Strong foundation in Python for data analysis, scripting, automation, or prototyping, with exposure to libraries such as pandas, NumPy, scikit-learn, or comparable tools - Working knowledge of SQL and relational data concepts, including joins, aggregation, filtering, and practical data exploration
- Strong foundation in Python for data analysis, scripting, automation, or prototyping, with exposure to libraries such as pandas, NumPy, scikit-learn, or comparable tools - Working knowledge of SQL and relational data 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
- Familiarity with software development practices such as Git, notebooks, code review, documentation, testing, and reproducible workflows - Familiarity with cloud platforms such as Azure or comparable environments is helpful but not required - Ability to learn new tools quickly and use AI-assisted development responsibly without treating generated output as automatically correct

Your next step

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

The Brattle Group, a privately held, global economics consulting firm, is looking for a Data and AI Engineer to join our Boston, MA office in July 2027.

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.

 

Where This Role Sits at Brattle:

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.

 

Nature of the Work:

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.

 

Some of the day-to-day responsibilities of this role include:

  • 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 problem
  • Contribute to workflows involving text extraction, classification, summarization, embeddings, retrieval-augmented generation, model evaluation, automation, visualization, or 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 helping prototype, test, and evaluate new tools, methods, and workflows before they are adopted more broadly
  • 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
  • Help turn lessons from project work and applied R&D into reusable team assets, examples, templates, documentation, and training materials

You will not be expected to own full workstreams on day one, but you will be expected to learn quickly, take initiative, and stretch beyond a narrow technical lane.

 

THE CANDIDATE

  • 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 also 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 methods, or automation to solve practical problems, with willingness to learn how to evaluate those tools responsibly
  • Comfort working in ambiguous problem spaces where the task may need to be clarified, decomposed, and revised as new information emerges
  • Strong foundation in Python for data analysis, scripting, automation, or prototyping, with exposure to libraries such as pandas, NumPy, scikit-learn, or comparable tools
  • Working knowledge of SQL and relational data 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 or heterogeneous data sources
  • Familiarity with software development practices such as Git, notebooks, code review, documentation, testing, and reproducible workflows
  • Familiarity with cloud platforms such as Azure or comparable environments is helpful but not required
  • Ability to learn new tools quickly and use AI-assisted development responsibly without treating generated output as automatically correct
  • Strong written and verbal communication skills, including the ability to explain technical work, assumptions, limitations, and next steps clearly
  • Ability to manage multiple parallel workstreams in a fast-paced environment
  • Flexible mindset to adapt to changing project priorities and client needs

 

Brattle offers a competitive benefits package, base salary, and bonus program for eligible roles based on individual and firm performance. The anticipated base gross salary range for this position in Boston, MA is $91,000 - $115,000 annually.  Actual salary will depend on a variety of factors, including experience and training.

 

This position is not eligible for immigration sponsorship.

 

EQUAL OPPORTUNITY

The Brattle Group is an Equal Opportunity Employer.  All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, citizenship status, national origin, ancestry, sex, gender identity and expression, age, height, weight, domestic partner status, Acquired Immune Deficiency Syndrome or HIV status (AIDS/HIV status), genetic information, sexual orientation, disability (where the applicant or employee is qualified to perform the essential functions of the job with or without reasonable accommodation), marital status, veteran status, political affiliation, drug or alcohol abuse or alcoholism, or any other characteristic protected under applicable law.

 

We encourage all applicants to click here to review our full Equal Employer Opportunity Statement.

 

THE EMPLOYER

The Brattle Group answers complex economic, finance, and regulatory questions for corporations, law firms, and governments around the world. We are distinguished by the clarity of our insights and the credibility of our experts, which include leading international academics and industry specialists. Brattle has 500 talented professionals across North America, Europe, and Asia-Pacific. For more information, please visit brattle.com​.​​​​​

 

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Pay
Flexible mindset to adapt to changing project priorities and client needs Brattle offers a competitive benefits package, base salary, and bonus program for eligible roles based on individual and firm performance. The anticipated base gross salary range for this position in Boston, MA is $91,000 - $115,000 annually. Actual salary will depend on a variety of factors, including experience and training. This position is not eligible for immigration sponsorship.
Location & working pattern

Boston, Massachusetts, United States

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