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Data Science Manager - AI

Agile Brains Consulting IncNew York, NY🇺🇸United StatesPosted 6 Sept 2026

Why This Role Stands Out

This role offers incredible growth potential, allowing you to lead impactful AI and data science initiatives for a major enterprise client while honing your technical and leadership skills. You'll thrive here if you're a seasoned data professional with strong client-facing experience and a passion for mentoring teams. Embrace this opportunity to shape innovative solutions and advance your career.

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
New York, NY, United States
Posted
19 hours ago
AWSMLOpsMachine LearningSnowflakeAgileAzureDatabricksGenerative AIStakeholder Management

Job Description

Work Arrangement: Hybrid – 2 days per week onsite

Position Overview

Agile Brains is seeking an experienced Data Science Manager – Data Engineering & AI to support a major enterprise client and provide technical and account leadership across a growing portfolio of Data Engineering, Advanced Analytics, Data Science, Machine Learning, and Generative AI initiatives.

This is a senior, client-facing leadership role combining technical leadership, delivery oversight, team management, and account ownership. The Data Science Manager will serve as the primary Agile Brains leader for the client’s Data and AI portfolio, working closely with client executives, business leaders, architects, data teams, and delivery teams to ensure initiatives are technically sound, effectively executed, and aligned with business priorities.

The ideal candidate brings strong technical credibility in data and AI while also possessing the executive presence and communication skills required to serve as a trusted advisor to the client.

Key Responsibilities

Data & AI Technical Leadership

  • Provide technical leadership across the client’s portfolio of Data Engineering, Analytics, Data Science, ML, Generative AI, and AI-enabled application initiatives.
  • Lead and mentor multidisciplinary teams including data engineers, data scientists, AI/ML engineers, analysts, architects, and other technical resources.
  • Partner with client architects and technology leaders to evaluate solution approaches, architecture, data requirements, integrations, and implementation options.
  • Guide teams in translating business problems into practical data, analytics, and AI solutions.
  • Provide technical oversight from initial discovery and proof-of-concept through engineering, testing, deployment, and production adoption.
  • Promote scalable engineering practices rather than isolated prototypes or one-off AI solutions.
  • Ensure appropriate consideration of data quality, security, privacy, governance, model performance, responsible AI, and production support requirements.
  • Conduct technical reviews and help teams resolve complex data, architecture, engineering, and AI challenges.

Delivery & Portfolio Leadership

  • Oversee delivery across multiple concurrent Data and AI initiatives.
  • Partner closely with Technical Program Managers, Product Owners, business stakeholders, and technical leads to ensure successful execution.
  • Maintain visibility into portfolio priorities, milestones, technical dependencies, risks, resource requirements, and delivery commitments.
  • Identify potential delivery or technical issues early and drive teams toward resolution.
  • Help establish appropriate delivery standards and operating practices across the Data and AI portfolio.
  • Ensure proofs-of-concept and experiments have clear criteria for determining whether they should be scaled, productionized, modified, or stopped.
  • Drive the transition from experimentation to sustainable, production-ready capabilities.
  • Ensure technical delivery remains connected to measurable business outcomes.

Client & Account Leadership

  • Serve as the primary Agile Brains account lead for Data Engineering and AI initiatives.
  • Develop strong relationships with client executives, technology leaders, business stakeholders, and technical teams.
  • Act as a trusted advisor to client leadership on Data, Analytics, and AI strategy, capabilities, delivery, and emerging opportunities.
  • Maintain an understanding of the client's business priorities and proactively identify opportunities where Data and AI can deliver additional value.
  • Coordinate Agile Brains resources supporting the account and ensure consistent quality across engagements.
  • Provide leadership with clear visibility into portfolio health, accomplishments, risks, resource needs, and upcoming priorities.
  • Facilitate executive and technical discussions and translate complex technology topics into clear business implications.
  • Support solution development, estimation, staffing, and planning for new Data and AI initiatives.
  • Partner with client leadership to develop a longer-term roadmap for expanding Data and AI capabilities.
  • Ensure Agile Brains consistently delivers a high-quality client experience and measurable business value.

Team Leadership

  • Provide day-to-day leadership, coaching, and technical direction to Agile Brains Data and AI resources supporting the client.
  • Establish clear expectations for quality, accountability, collaboration, and delivery.
  • Mentor technical team members and support their professional development.
  • Assist with interviewing and selecting Data Engineering, Data Science, AI/ML, and related technical resources.
  • Ensure teams collaborate effectively across business, product, architecture, engineering, infrastructure, security, and operations.
  • Build a culture focused on technical excellence, ownership, continuous learning, and client outcomes.

Required Qualifications

  • 10+ years of experience across Data Science, Data Engineering, Analytics, AI/ML, or related technology disciplines, including significant technical leadership experience.
  • 5+ years of experience leading technical teams and complex enterprise Data, Analytics, or AI initiatives.
  • Strong understanding of modern data architecture, data engineering, analytics, machine learning, and AI solution development.
  • Experience delivering solutions using modern cloud-based data and AI platforms.
  • Demonstrated ability to lead initiatives from business problem identification through architecture, engineering, implementation, and production adoption.
  • Strong understanding of data pipelines, integration, data quality, governance, analytics, ML/AI lifecycle, and production operations.
  • Experience with Generative AI, LLMs, RAG, AI agents, or other modern AI architectures is highly desirable.
  • Demonstrated ability to manage and mentor highly technical resources.
  • Experience working directly with senior client and business stakeholders.
  • Excellent written, verbal, presentation, and facilitation skills.
  • Ability to explain complex Data and AI concepts to both technical and non-technical audiences.
  • Strong executive presence and ability to operate as a trusted advisor.
  • Demonstrated ability to manage multiple initiatives and priorities simultaneously.
  • Ability to work onsite two days per week.

Preferred Qualifications

  • Previous experience within the utilities, energy, infrastructure, or another highly regulated industry.
  • Experience leading a portfolio containing a combination of Data Engineering, traditional Data Science/ML, Generative AI, and advanced analytics projects.
  • Experience with cloud data and AI ecosystems such as Azure, AWS, Databricks, Snowflake, or equivalent platforms.
  • Familiarity with MLOps, LLMOps, model evaluation, AI governance, data governance, and responsible AI practices.
  • Experience working with enterprise data platforms and large, complex datasets.
  • Consulting or professional-services experience with responsibility for both client relationships and technical delivery.
  • Experience supporting account growth, solution development, resource planning, and executive stakeholder management.

What Success Looks Like

Success in this position goes beyond completing individual projects. The Data Science Manager will establish a strong, trusted relationship with the client and create a cohesive Data and AI delivery capability across the account.

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