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Manager, Data Science

Job in Raleigh, Wake County, North Carolina, 27608, USA
Listing for: Kelly Services
Full Time position
Listed on 2026-10-11
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Science Manager
Job Description & How to Apply Below
$90 - $100

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, Lang Chain/Lang Graph, ML frameworks (e.g. Tensor Flow, PyTorch) and prompt…
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