Manager, Data Science

Raleigh, NC, US • Posted 11 hours ago • Updated 11 hours ago
Contract W2
On-site
$90 - $100/hr
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Fitment

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Job Details

Skills

  • IT Strategy
  • Streaming
  • Research
  • Science
  • Benchmarking
  • Rapid Prototyping
  • Customization
  • Roadmaps
  • Scalability
  • Writing
  • Prototyping
  • Operational Excellence
  • Adaptability
  • Mentorship
  • Accountability
  • Collaboration
  • Product Engineering
  • Legal
  • Innovation
  • Knowledge Sharing
  • Continuous Improvement
  • Computer Science
  • Statistics
  • Data Science
  • Management
  • Team Management
  • Leadership
  • Python
  • LangChain
  • TensorFlow
  • PyTorch
  • Routing
  • Vector Databases
  • Unstructured Data
  • Workflow
  • Machine Learning (ML)
  • Continuous Integration
  • Continuous Delivery
  • RESTful
  • Evaluation
  • IaaS
  • Amazon Web Services
  • Microsoft Azure
  • Google Cloud
  • Google Cloud Platform
  • Artificial Intelligence
  • GitHub

Summary

Job Title: Manager Of Data Science

Location: 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 strongly preferred, or equivalent practical experience
  • Bachelor's degree in a relevant field with significant applied experience in data science, machine learning, or AI
  • Typically requires:
  • 8+ years of relevant experience in data science, machine learning, or applied AI
  • 4+ years of leadership experience (direct or indirect team management)

We recognize that exceptional candidates may follow non-traditional paths and value demonstrated impact, technical depth, and leadership over strict credential requirements.
Technical Proficiency
  • Proficient with Python, ML and LLM tooling such as Google ADK, LangChain/LangGraph, ML frameworks (e.g. TensorFlow, PyTorch) and prompt tuning techniques
  • Experience building multi-agent or orchestrated LLM systems - task decomposition, tool use, routing, state and failure handling
  • Familiarity with vector databases, knowledge graphs, and hybrid retrieval architecture
  • Strong experience working with structured and unstructured data at scale
  • Ability to design and implement data pipelines and preparation workflows
  • Experience integrating ML into complex, multi-stage processing systems, including event-driven architectures
  • Working knowledge of containerization, CI/CD, RESTful API design and model serving tools
  • Familiarity with LLM observability and evaluation tooling (tracing, offline eval harnesses, LLM-as-judge and human review pipelines)
  • Cloud infrastructure experience on AWS (preferred), Azure, or Google Cloud Platform
  • Familiarity with AI coding tools (e.g. GitHub Copilot, Claude Code, OpenAI Codex)
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10105282
  • Position Id: 886174
  • Posted 11 hours ago

Company Info

About Motion Recruitment Partners, LLC

Motion Recruitment delivers IT Talent Solutions for Contract, Direct Hire, Managed Solutions and Statement of Work to all of North America from our 21 delivery centers. Our high-touch, specialized, team-based recruitment model’s success is proven through our exemplary track record in filling the most challenging IT positions for startup and enterprise clients alike. Our hyper-specialized tech focus results in a truly consultative approach for both our clients and candidates, within our recruiting areas of expertise: Software, Mobile, Data, Infrastructure, Cybersecurity, Product + UX and Functional.

Motion also delivers IT Consulting Solutions through the Motion Consulting Group (MCG) that create true digital transformation for IT projects in Agile Development & Coaching, DevOps & DevSecOps Solutions, and Managed Services for IT Operations.

We’re also the proud creators of Tech in Motion and the Timmy Awards, our North American community platform, events series and award program that connects over 250,000 tech enthusiasts to meet, learn, and innovate.

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