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Manager, Data Science

Job in Raleigh, Wake County, North Carolina, 27601, USA
Listing for: Motion Recruitment
Full Time position
Listed on 2026-10-10
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Data Science Manager
Job Description & How to Apply Below

Manager Of Data Science

Raleigh, NC (27606)

Duration: 6 Months (Contract to Hire)

Role Overview:
We are seeking a hands-on Manager of Data Science to lead a high-impact team on our Agentic Content Platform — building the shared agents, evaluation, and platform core capabilities that run our content streams, and owning the delivery of some streams end to end. This is a player-coach role combining people's leadership, technical strategy, and selective hands-on data science contribution.

Key Responsibilities Scope & Impact:

  • Set the vision and strategic priorities for AI across the content platform, acting as a recognized expert for Data Science
  • Own delivery of your assigned content streams — quality, timeliness, and automation level — while contributing reusable capability back to the shared platform
  • Lead and develop a team of data scientists, setting the cultural tone for the group
  • Drive applied research with a clear path to production, keeping the business outcome as the first priority and working within real-world constraints such as latency and reliability
  • Build and scale evaluation science capabilities within the team, including offline evaluation frameworks, automated benchmarking pipelines, and human-in-the-loop feedback systems to rigorously measure model quality and business impact
  • Champion hands-on rapid prototyping and iteration
  • Collaborate with other Data Science teams to maximize re-use of components and patterns, eliminating waste, duplication and unnecessary customization
  • Operate with broad scope, coordinating across multiple cross-functional teams, systems, and domains
  • Exercise judgment about where to automate, where to keep a human editor in the loop, and how to move that line over time
  • Select the right tools and technologies for the business problem

Technical & Product Leadership:

  • Define and execute the AI roadmap for the content platform, prioritizing reusable platform capabilities and agent-based workflows over one-off solutions.
  • Translate ambiguous business problems into clear technical strategies and delivery plans, identifying tradeoffs and alternative approaches when constraints arise.
  • Design and oversee production-grade AI systems that meet customer requirements for accuracy, reliability, scalability, and appropriate human oversight.
  • Partner with Product, Engineering, and Architecture leaders to establish shared foundations, integrate AI into the platform at scale, and replace bespoke tooling with reusable workflows.
  • Lead by example through hands-on technical contributions, including writing code, developing and demonstrating prototypes, and contributing to experiments and production models.
  • Establish and scale Data Science standards for experimentation, evaluation, deployment, monitoring, performance, and reliability across both the team's solutions and shared capabilities.

Team & Operational Excellence:

  • Foster a culture of curiosity, adaptability, responsible innovation, knowledge sharing, and continuous learning, enabling the team to evolve as technologies, customer needs, and business priorities change.
  • Build, mentor, and develop a high-performing data science team, supporting individual growth and career development.
  • Establish clear goals, priorities, operating rhythms, and accountability for the team's work.
  • Foster effective collaboration across Product, Engineering, Design, Legal, and other business functions.
  • Promote a culture of technical excellence, responsible innovation, knowledge sharing, and continuous improvement.
  • Ensure the team has the skills, resources, and organizational support needed to deliver against business priorities.

Core Qualifications Experience &

Education:

  • Advanced degree (Master's or PhD) in Data Science, Computer Science, Statistics, or a related field…
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