Data Scientist
Next League, LLC
| Company | Next League, LLC |
| Category | Data & Analytics |
| Location | United States |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 15 May 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
This role begins as a contract position at an hourly rate of $200 USD per hour , providing a streamlined path toward a permanent, salaried full-time transition. Please note that while the contract phase offers a higher hourly rate in lieu of benefits, the full-time conversion introduces a comprehensive total rewards package, including premium health coverage and retirement programs, alongside a restructured annual salary.
Next League is seeking a Data Scientist to join the AI Strategy, Training and Transformation team. This role pairs rigorous applied data science with hands-on AI agent prototyping to power how we deliver measurable outcomes for our sports, entertainment, and league clients.
The role sits at the intersection of quantitative modeling and applied AI engineering. You will design and ship models that drive revenue, marketing performance, fan engagement, and operational efficiency, while also prototyping AI agents and applied AI tooling that scale our delivery across client accounts. You will collaborate primarily with product, strategy, and engineering counterparts, with occasional embedding on client engagements to lead technical discovery, audit data, and architect modeling solutions. Clients include professional teams, leagues, major sports properties, and national governing bodies.
Projects may span:
Predictive and propensity modeling (fan churn, lookalike audiences, conversion likelihood, lifetime value)
Marketing performance, attribution, and media mix modeling
Pricing, demand forecasting, and inventory optimization for ticketing and hospitality
Recommendation and personalization systems for fan-facing experiences
AI agent prototypes for sales, service, content, and internal workflows
Evaluation frameworks for LLM and agentic systems (accuracy, latency, cost, safety, drift)
Custom analytics and insight tooling for Next League consultants and client stakeholders
Essential Duties and Responsibilities
The following and other duties may be assigned as necessary:
Modeling & Applied Data Science
Design, build, and deploy machine learning and statistical models that address client business challenges across revenue, marketing, and fan engagement
Lead exploratory data analysis, feature engineering, and model selection across structured and unstructured client data
Translate ambiguous business problems into well-scoped modeling initiatives with clear success metrics
Build evaluation frameworks and monitor model performance, drift, and business impact over time
Document modeling decisions, assumptions, and tradeoffs in a way that earns trust with both technical and non-technical stakeholders
AI Agent & Applied AI Development
Prototype AI agents, copilots, and assistants using leading frameworks such as LangChain, LangGraph, OpenAI Agents SDK, and Claude
Build retrieval-augmented (RAG) pipelines and tool-using agent workflows for internal and client use cases
Develop evaluation rubrics for agent quality covering accuracy, latency, cost, and safety guardrails
Partner with engineering to harden prototypes into production-ready solutions
Stay current on the rapidly evolving model and tooling landscape, and bring practical recommendations back to the team
Client & Team Collaboration
Support AI Product Managers and consultants with quantitative analysis, modeling, and technical deep-dives
Occasionally embed with client teams to lead data audits, modeling workshops, and technical architecture discussions
Communicate complex modeling results to non-technical stakeholders with clarity and credibility
Contribute to executive-ready deliverables including business cases, demos, and rollout plans
Tooling, Productization, and Governance
Help shape Next League's internal data science and AI tooling stack
Build repeatable patterns that scale modeling and agent work across the client portfolio, including notebooks, evaluation harnesses, pro
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