Data Scientist (AI)

TL;DR

Data Scientist (AI): Design and deploy machine learning models and AI agent prototypes for sports, entertainment, and league clients with an accent on predictive modeling, marketing analytics, and fan engagement systems. Focus on building RAG pipelines, evaluation frameworks for LLMs and agents, and scalable tooling for revenue optimization and operational efficiency.

United States

$200 USD per hour (contract position transitioning to full-time salaried with benefits)

Company

Sports, entertainment, and league-focused firm delivering AI-driven outcomes for professional teams, leagues, and governing bodies.

What you will do

• Design, build, and deploy ML/statistical models for revenue, marketing, fan engagement, pricing, and personalization.
• Prototype AI agents, copilots, RAG pipelines, and tool-using workflows using LangChain, OpenAI Agents, and similar frameworks.
• Lead exploratory data analysis, feature engineering, model evaluation, and performance monitoring.
• Collaborate with product managers, engineers, and client teams on technical discovery, audits, and architecture.
• Develop repeatable tooling, notebooks, prompt libraries, and governance standards for scaling across clients.
• Communicate results and recommendations to technical and non-technical stakeholders.

Requirements

• 3-5 years in data science, applied ML, or quantitative analytics.
• Strong statistics, ML, experimental design; proficiency in Python, SQL, and one ML library (scikit-learn, PyTorch, TensorFlow, XGBoost).
• Experience deploying models to real business problems with outcomes.
• Hands-on with LLMs and at least one agent/RAG framework.
• Product instincts for shipping pragmatic solutions under timelines; exceptional communication.
• Comfort in ambiguity, responsible AI, governance, and data handling.

Nice to have

• Sports, entertainment, league, media, or performance marketing experience.
• AI platforms: Claude, OpenAI APIs, Google Gemini, Microsoft Copilot, AWS Bedrock, Azure AI.
• Agent frameworks (LangGraph, CrewAI), vector DBs (Pinecone, Weaviate), cloud platforms (Snowflake, BigQuery).
• Marketing/CRM/ticketing systems, automation tools (n8n, Zapier), MLOps.

Culture & Benefits

• Hands-on role blending modeling, AI prototyping, and client collaboration.
• Full-time transition includes premium health coverage and retirement programs.
• Pragmatic environment for builders thriving in notebooks and client meetings.
• Focus on shipping applied AI with analytical rigor for measurable client impact.