Manager - Data Science & AI Consulting

Arthur D. Little Services S.A.S.

• $150K — $180K *
Business Services
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of hands-on experience in artificial intelligence and machine learning solutions
  • Strong proficiency in Python and SQL for data manipulation
  • Familiarity with AI frameworks (e.g., PyTorch, Hugging Face) and cloud environments (e.g., AWS, Google Cloud)
  • Demonstrated leadership in managing and mentoring technical teams while contributing personally to projects
  • Background in consulting, ideally with direct client engagement and relationship-building experience
  • Practical knowledge in data architecture, integration, and performance improvement for AI solutions

Responsibilities

  • Lead full-cycle AI and data science projects from conception to delivery
  • Serve as a player-coach, merging leadership with hands-on technical contributions
  • Rapidly prototype AI solutions to validate concepts and accelerate client adoption
  • Design scalable solution architectures and make data-driven technical decisions
  • Work collaboratively with client teams to transition projects from ideation to production
  • Review code and provide technical guidance to ensure solution quality and effectiveness
  • Cultivate client relationships to define strategies and turn analytical insights into actionable results

Benefits

  • Comprehensive health and wellness benefits
  • Flexible working environment with options for remote work
  • Professional development opportunities and mentorship programs
  • Collaborative team culture with a focus on innovation
  • Access to cutting-edge technologies and projects across various industries
Full Job Description
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.

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.

 

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