Manager - Data Science & AI Consulting

Arthur D. Little Services S.A.S.•New York, NY

3d•Onsite

About The Position

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. 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.

Requirements

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.
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.

Responsibilities

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.