Data Science Manager
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Role details
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Job description
We are seeking a hands-on Manager of Data Science to lead a high-impact team building shared agents, evaluation frameworks, and platform core capabilities for an agentic content platform. This is a player-coach role combining people leadership, technical strategy, and selective hands-on data science contribution, with ownership over budgets, forecasting, planning, and resourcing. The ideal candidate has meaningful experience designing, architecting, and implementing an agentic RAG-based system, and can translate complex technical concepts into clear language for business partners. Key Responsibilities Scope & Strategic Impact
- Set the vision and strategic priorities for AI across the content platform, acting as a recognized expert for Data Science.
- Own delivery of assigned content streams - quality, timeliness, and automation level - while contributing reusable capability back to the shared platform.
- Drive applied research with a clear path to production, prioritizing business outcomes within real-world constraints such as latency and reliability.
- Build and scale evaluation science capabilities, including offline evaluation frameworks, automated benchmarking pipelines, and human-in-the-loop feedback systems.
- Collaborate with other Data Science teams to maximize reuse of components and eliminate duplication.
Technical & Product Leadership
- Define and execute the AI roadmap for the content platform, prioritizing reusable platform capabilities and agent-based workflows.
- Translate ambiguous business problems into clear technical strategies and delivery plans.
- Design and oversee production-grade AI systems meeting requirements for accuracy, reliability, scalability, and human oversight.
- Partner with Product, Engineering, and Architecture leaders to integrate AI into the platform at scale.
- Lead by example through hands-on technical contributions, including writing code and developing prototypes.
- Establish and scale Data Science standards for experimentation, evaluation, deployment, and monitoring.
Team & Operational Excellence
- Build, mentor, and develop a high-performing data science team, supporting career growth.
- Establish clear goals, priorities, operating rhythms, and accountability for the team’s work.
- Foster effective collaboration across Product, Engineering, Design, and other business functions.
- Oversee budgets, forecasting, planning, and resourcing for the team.
- Promote a culture of curiosity, responsible innovation, and continuous learning.
Requirements
Senior/Managerial Level (8+ years of relevant data science/ML experience; 4+ years of leadership experience)., * 8+ years of relevant experience in data science, machine learning, or applied AI.
- 4+ years of leadership experience (direct or indirect team management).
- Advanced degree (Master’s or PhD) in Data Science, Computer Science, Statistics, or a related field strongly preferred; equivalent practical experience also considered.
- Demonstrated experience designing, architecting, and implementing an agentic RAG-based system, with evidence of meaningful technical decision-making.
- Proficiency with Python and ML/LLM tooling (e.g., LangChain/LangGraph, TensorFlow, PyTorch, prompt tuning techniques).
- Experience building multi-agent or orchestrated LLM systems, including task decomposition, tool use, routing, and failure handling.
- 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.
- Cloud infrastructure experience on AWS, Azure, or GCP.
- Strong communication skills, with the ability to explain complex concepts to business partners in clear, non-technical language.
Preferred Qualifications
- Familiarity with vector databases, knowledge graphs, and hybrid retrieval architecture.
- Working knowledge of containerization, CI/CD, RESTful API design, and model serving tools.
- Familiarity with LLM observability and evaluation tooling, including tracing, offline evaluation harnesses, and LLM-as-judge/human review pipelines.
- Familiarity with AI coding assistants (e.g., GitHub Copilot or similar tools).
Core Skills & Attributes
- Strong player-coach mindset, balancing people leadership with hands-on technical contribution.
- Excellent ability to translate complex technical concepts into clear, jargon-free language for business stakeholders.
- Strong judgment in balancing automation with human oversight in AI system design.
- Proven ability to build and scale high-performing technical teams.
- Collaborative leadership style across cross-functional teams and domains.
- Comfortable operating with broad scope across multiple systems and business priorities.
Benefits & conditions
- Competitive salary, SMART TECH SKILLS LLC
-
Tallahassee, FL Benefits: Competitive salary Location Starts as remote, later changing to hybrid in Raleigh, NC (relocation required; candidates able to relocate at the start of the contract…
- 14 hours ago + *
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