Data Science Manager

Smart Tech Skills LLC; Raleigh (NC); Hybrid; USD 180,000 - 230,000; Full time

Benefits offered by this job

Remote work

Relocation assistance

Job summary

Smart Tech Skills LLC seeks a hands-on Manager of Data Science to lead a high-impact team developing shared agents, evaluation frameworks, and platform core capabilities for an agentic content platform. This player-coach role includes budget ownership, forecasting, planning, and resourcing, plus hands-on data science contributions.

The ideal candidate has 8+ years in data science/ML and 4+ years in leadership, with experience designing agentic RAG-based systems and translating technical concepts

Qualifications

• 8+ years of relevant data science, ML, or applied AI experience.
• 4+ years in leadership (direct or indirect).
• Advanced degree strongly preferred; equivalent practical experience considered.
• Experience designing and implementing agentic RAG-based systems with technical decision-making.
• Proficiency with Python and ML/LLM tooling.
• Experience building multi-agent or orchestrated LLM systems.
• Strong experience with structured and unstructured data at scale.
• Ability to design data pipelines and preparation workflows.
• Experience integrating ML into complex, multi-stage processing systems.
• Cloud infrastructure experience on AWS, Azure, or GCP.
• Strong communication skills to translate technical concepts to business partners.

Responsibilities

• Set vision and strategic AI priorities for the content platform as Data Science lead.
• Own delivery of content streams with quality and automation, while contributing reusable capabilities.
• Drive applied research with production paths focused on latency and reliability.
• Build and scale evaluation science capabilities, including offline evaluation pipelines.
• Collaborate with other Data Science teams to maximize component reuse.
• Define and execute the AI roadmap and scalable agent-based workflows.
• Translate business problems into clear technical strategies and delivery plans.
• Design production-grade AI systems with accuracy, reliability, and human oversight.
• Partner with Product, Engineering, and Architecture to scale AI integration.
• Lead by example with hands-on technical contributions and prototypes.
• Establish Data Science standards for experimentation and monitoring.
• Build and mentor a high-performing data science team.
• Set goals, rhythms, and accountability for the team.
• Foster cross-functional collaboration across Product, Engineering, Design, and business.

Skills

Data Science Leadership

Agent-based AI

Python & ML tooling

RAG systems

Multi-agent orchestration

Cloud platforms

Business communication

Budgeting & resourcing

Education

Master's or PhD in Data Science/CS/Stats

Tools

LangChain/LangGraph

TensorFlow

PyTorch

CI/CD

Model serving tools

Job description

Benefits:

• Competitive salary

Location

Starts as remote, and later becomes hybrid in Raleigh, NC (relocation required; candidates able to relocate at the start of the contract are preferred, though relocation may occur upon conversion to full-time).

Experience Level

Senior/Managerial Level (8+ years of relevant data science/ML experience; 4+ years of leadership experience).

Role Overview

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

• 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.

Required Qualifications

• 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.

This is a remote position.