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Manager - Data Science & AI Consulting

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What you’ll work on

Full posting

Arthur D. Little (ADL) is seeking a Manager - Data Science & AI Consulting to join our SPACE team.

The successful candidate will work directly with clients to identify high-value opportunities for artificial intelligence, rapidly translate business problems into technical solutions, and lead multidisciplinary teams through implementation.

  • Lead end-to-end AI and data science engagements, from problem framing to delivery

  • Rapidly prototype and build AI and machine learning solutions to validate value

  • Review code and technical designs, and troubleshoot difficult implementation problems

  • Manage, mentor, and develop multidisciplinary teams while staying involved in delivery

  • Advise senior client stakeholders and turn data insights into recommendations

From the employer’s posting
Arthur D. Little (ADL) is seeking a Manager - Data Science & AI Consulting to join our SPACE team. This is a player-coach role for an experienced artificial intelligence practitioner who combines deep technical expertise with strong consulting, leadership, and interpersonal skills.
The successful candidate will work directly with clients to identify high-value opportunities for artificial intelligence, rapidly translate business problems into technical solutions, and lead multidisciplinary teams through implementation. They are expected to remain hands-on with technology - architecting solutions, prototyping, reviewing code, and solving difficult technical problems - while simultaneously managing teams and advising senior client stakeholders.
Lead end-to-end artificial intelligence and data science engagements - from problem framing and model design through prototyping, implementation, and delivery.
Rapidly prototype and build artificial intelligence and machine learning solutions to demonstrate feasibility, validate value, and accelerate client adoption.
Review code and technical designs, troubleshoot difficult implementation problems, and provide technical direction to delivery teams.
Manage, mentor, and develop multidisciplinary teams of internal and external data scientists, engineers, and consultants while remaining actively involved in delivery.
Partner with clients to define data-driven strategies, identify value-creation opportunities, and translate analytical insights into actionable recommendations.

What you’ll bring

All qualifications

Core experience

  • Experience may include PyTorch, scikit-learn, Hugging Face, LangChain, LlamaIndex, vector or graph databases, Databricks, Microsoft Azure, Amazon Web Services, or Google Cloud.
  • Knowledge systems: Practical understanding of retrieval-augmented generation, semantic search, vector databases, graph databases, and knowledge graph approaches.
  • Leadership: Demonstrated ability to lead multidisciplinary teams while remaining actively involved in delivery.
Qualification wording
Modern artificial intelligence stack: Hands-on experience with relevant frameworks, model providers, knowledge systems, data platforms, and cloud environments. Experience may include PyTorch, scikit-learn, Hugging Face, LangChain, LlamaIndex, vector or graph databases, Databricks, Microsoft Azure, Amazon Web Services, or Google Cloud. Specific technologies are less important than demonstrated ability to learn and apply the right tools quickly.
Knowledge systems: Practical understanding of retrieval-augmented generation, semantic search, vector databases, graph databases, and knowledge graph approaches.
Leadership: Demonstrated ability to lead multidisciplinary teams while remaining actively involved in delivery. Able to coach junior technical talent, raise the quality of their work, and create an effective collaborative environment.

Posting record

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Status in our records
Live
First seen by us
Oct 2, 202642 days ago
Recorded sightings
32
Last seen by us
Nov 13, 2026
Employer says posted
Sep 29, 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

Time since we first saw it

Day 42

Similar jobs usually come down between day 4 and day 77.

At Arthur D. Little Services S.A.S., jobs usually come down by about day 46.

From 51 similar postings that came down, and 7 of Arthur D. Little Services S.A.S.’s. Coming down is not always a hire.

Arthur D. Little Services S.A.S. is hiring

1 open job

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring has slowed
  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

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  • Python
  • Azure
  • Databricks
  • Hugging Face
  • PyTorch
  • scikit-learn
  • SQL
  • AWS
  • GCP
Where the posting names them
- Artificial intelligence engineering: Ability to take solutions from experimentation and prototyping through production implementation, including architecture, integration, testing, monitoring, and performance improvement. - Programming: Advanced Python skills and strong proficiency working with data and Structured Query Language. Candidates should be comfortable personally developing prototypes, reviewing production code, and troubleshooting technical issues. - Modern artificial intelligence stack: Hands-on experience with relevant frameworks, model providers, knowledge systems, data platforms, and cloud environments. Experience may include PyTorch, scikit-learn, Hugging Face, LangChain, LlamaIndex, vector or graph databases, Databricks, Microsoft Azure, Amazon Web Services, or Google Cloud. Specific technologies are less important than demonstrated ability to learn and apply the right tools quickly.
- Programming: Advanced Python skills and strong proficiency working with data and Structured Query Language. Candidates should be comfortable personally developing prototypes, reviewing production code, and troubleshooting technical issues. - Modern artificial intelligence stack: Hands-on experience with relevant frameworks, model providers, knowledge systems, data platforms, and cloud environments. Experience may include PyTorch, scikit-learn, Hugging Face, LangChain, LlamaIndex, vector or graph databases, Databricks, Microsoft Azure, Amazon Web Services, or Google Cloud. Specific technologies are less important than demonstrated ability to learn and apply the right tools quickly. - Knowledge systems: Practical understanding of retrieval-augmented generation, semantic search, vector databases, graph databases, and knowledge graph approaches.

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Demand for AI Engineer roles

New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.

Weekly new AI Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 7, the most 65, and the latest week had 65.
August 17Last week

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Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

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

AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.

Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.

An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.

Job description

View original posting ↗

Overview

Location: Boston or New York City

Practice: SPACE (Digital and Artificial Intelligence)

Reports To: Partner - Digital & AI Solutions, Americas

 

About the Role

 

Arthur D. Little (ADL) is seeking a Manager - Data Science & AI Consulting to join our SPACE team. This is a player-coach role for an experienced artificial intelligence practitioner who combines deep technical expertise with strong consulting, leadership, and interpersonal skills.

 

The successful candidate will work directly with clients to identify high-value opportunities for artificial intelligence, rapidly translate business problems into technical solutions, and lead multidisciplinary teams through implementation. They are expected to remain hands-on with technology - architecting solutions, prototyping, reviewing code, and solving difficult technical problems - while simultaneously managing teams and advising senior client stakeholders.

 

The role sits at the intersection of a forward-deployed artificial intelligence engineer, technical product leader, and management consultant: someone equally comfortable working alongside engineers and data scientists or leading a discussion with client executives.

Why Join ADL

At Arthur D. Little, you will work with a global network of industry experts, data scientists, engineers, and strategists driving digital transformation across sectors. The SPACE team is at the forefront of shaping how artificial intelligence and data redefine value creation, combining ADL's strategic heritage with deep technical expertise and hands-on delivery.

 

This role offers the opportunity to help clients move beyond artificial intelligence strategy and experimentation to build solutions that deliver measurable business impact - while developing teams, shaping client relationships, and contributing to the growth of ADL's artificial intelligence capabilities in the Americas.

Responsibilities

As a Manager at Arthur D. Little, you lead the successful accomplishment of our assignments. Therefore, you will:

  • Lead end-to-end artificial intelligence and data science engagements - from problem framing and model design through prototyping, implementation, and delivery.
  • Operate as a player-coach, combining project and team leadership with direct, hands-on contribution to solution design and development.
  • Rapidly prototype and build artificial intelligence and machine learning solutions to demonstrate feasibility, validate value, and accelerate client adoption.
  • Design solution architectures and make pragmatic technical choices across models, data, applications, and infrastructure.
  • Apply artificial intelligence, machine learning, and optimization techniques to address complex business challenges.
  • Work side-by-side with client technical teams, data scientists, engineers, and business leaders to move solutions from concept and prototype into production.
  • Review code and technical designs, troubleshoot difficult implementation problems, and provide technical direction to delivery teams.
  • Translate ambiguous client problems into well-defined technical approaches, balancing business value, technical feasibility, speed, and scalability.
  • Partner with clients to define data-driven strategies, identify value-creation opportunities, and translate analytical insights into actionable recommendations.
  • Manage, mentor, and develop multidisciplinary teams of internal and external data scientists, engineers, and consultants while remaining actively involved in delivery.
  • Build trusted relationships with senior client stakeholders and communicate complex technical concepts through clear, business-relevant narratives.
  • Support business development by identifying opportunities, shaping proposals, designing solutions, and leading client presentations.
  • Contribute to thought leadership and intellectual capital within ADL's SPACE practice, particularly in artificial intelligence, data strategy, and automation.
  • Collaborate closely with ADL's global industry practices, including Life Sciences, Automotive, Telecommunications, Media, and Consumer Goods, to embed artificial intelligence-driven value creation across sectors.

Qualifications

Required Skills and Experience
  • Hands-on artificial intelligence practitioner: Demonstrated track record personally designing, coding, and deploying artificial intelligence and machine learning solutions. This role is not intended for candidates whose recent experience has been primarily managing technical teams.
  • Artificial intelligence and machine learning: Deep practical experience across machine learning and modern generative artificial intelligence, including large language models, retrieval-augmented generation, agents, evaluation, and optimization.
  • Artificial intelligence engineering: Ability to take solutions from experimentation and prototyping through production implementation, including architecture, integration, testing, monitoring, and performance improvement.
  • Programming: Advanced Python skills and strong proficiency working with data and Structured Query Language. Candidates should be comfortable personally developing prototypes, reviewing production code, and troubleshooting technical issues.
  • Modern artificial intelligence stack: Hands-on experience with relevant frameworks, model providers, knowledge systems, data platforms, and cloud environments. Experience may include PyTorch, scikit-learn, Hugging Face, LangChain, LlamaIndex, vector or graph databases, Databricks, Microsoft Azure, Amazon Web Services, or Google Cloud. Specific technologies are less important than demonstrated ability to learn and apply the right tools quickly.
  • Knowledge systems: Practical understanding of retrieval-augmented generation, semantic search, vector databases, graph databases, and knowledge graph approaches.
  • Software development: Strong understanding of software engineering principles, including version control, testing, code quality, application integration, and agile delivery methods.
  • Client consulting: Strong ability to work directly with clients, structure ambiguous problems, facilitate working sessions, communicate with senior executives, and translate between business and technical stakeholders.
  • Leadership: Demonstrated ability to lead multidisciplinary teams while remaining actively involved in delivery. Able to coach junior technical talent, raise the quality of their work, and create an effective collaborative environment.
  • Commercial orientation: Ability to identify opportunities, shape solutions, contribute to proposals, and build trusted client relationships that lead to follow-on work.
  • Consulting experience: Prior experience in management consulting, professional services, technology consulting, or another client-facing delivery environment is highly preferred.
  • Industry background: Experience in Automotive, Telecommunications, Media, Consumer Goods, Life Sciences, or other relevant industries is advantageous.
Personal Attributes
  • A value-oriented technologist who is motivated by solving business problems, not technology for its own sake.
  • A people person with strong interpersonal skills who builds credibility quickly with clients and colleagues at all levels.
  • Comfortable moving fluidly between executive conversations, team leadership, technical architecture, and hands-on development.
  • A collaborative player-coach who enjoys developing others while remaining personally accountable for the quality of the work.
  • Naturally curious and able to learn new technologies, industries, and problem domains quickly.
  • A self-starter with entrepreneurial drive, resilience, sound judgment, and a bias toward action in ambiguous contexts.
  • A clear communicator who can translate complex technical ideas into compelling, business-relevant insights and narratives.

 

Arthur D. Little is an equal-opportunity employer. We are committed to ensuring that no employee, contractor, vendor, or job applicant is discriminated against because of their race, color, nationality, ethnic or national origin, religion or belief, sex, marital or civil partner status, veteran status, sexual orientation, age, gender reassignment, or disability.

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