Summary We are seeking a data scientist to be a leading contributor towards our demand modeling and product advancement efforts. As an early RightsHelper hire, you would help oversee and develop key components of our industry-leading RightsHelper platform. The ideal candidate has experience executing and maintaining accurate and interpretable models for pricing, forecasting, or marketing applications in a fast-paced, enterprise environment. Our platform provides a unique opportunity for data scientists to work closely with leading sports and live event organizations in developing innovative techniques and advancing their decision-making. Job Functions - Perform model calibration processes for our partner organizations; this includes externally interacting with partner analytics leaders and internally documenting, standardizing, and improving these processes. - Support partners in successfully delivering on their priorities, platform setup, and overall management of modeled deliverables. - Collaborate with other Data Science team members to push root-level improvements across demand modeling, sales forecasting, pricing, and ticket inventory optimization applications. - Maintain and improve upon codebase with version control, collaboration, and general software development best practices. - Provide input on product development, data collection, data architecture, front-end development, and general business strategy. - Help build a collaborative engineering culture focused on ownership and empathy for our customers.

• Work on the latest applications of data science to solve business problems • Work directly with client stakeholders to translate business problems into high level analytics solution designs • Present analytic solutions to business audiences highlighting robustness of the solution and how it could help generate business value • Develop end-to-end solutions based on in-depth understanding of business problems to ensure analytics solutions are delivered efficiently, predictably, and sustainably • Design and develop **machine learning and Generative AI solutions** using Databricks and Azure AI services. • Build **LLM-powered applications** leveraging Azure OpenAI and orchestrate workflows using **LangGraph** • Develop **agentic AI workflows** for automation, insights generation, and decision support • Implement **Document Intelligence solutions** for extracting insights from unstructured data • Participate in discussions with team members to select and apply relevant analytic techniques and create actionable business insights • Responsible for making presentations to senior management, communicating results to business teams, and develop plans to help operationalize analytic solution

• Coordinate 3–4 concurrent workstreams (data science, MLOps, engineering, front-end/back-end) and track progress against tight delivery timelines. • Align internal data science teams (Mexico, India, Spain, US) with partner S&T/engineering organizations. • Identify cross-functional blockers and drive proactive resolution to maintain schedule. • Represent the data science team in frequent S&T-led working sessions and executive updates. • Serve as primary liaison between data science teams, engineering/S&T teams and internal leadership. • Manage meeting cadence, follow-ups, execution tracking and action ownership. • Translate technical progress and risks into clear, concise status updates for stakeholders. • Ensure teams receive required data inputs, meet deliverables and coordinate dependencies. • Establish and manage workstreams, coordination processes and cross-team communication flows. • Drive accountability and orchestrate cross-team workflows without impeding execution velocity.

• Own Marketing Data Strategy, Architecture & CDP Ecosystem: Define and lead the end-to-end marketing data framework across collection, integration, unification, governance, activation, and measurement. • Ensure Data Integrity, Governance & Compliance: Establish lifecycle definitions, taxonomy standards, validation rules, identity frameworks, and consent management processes. • Build a Unified Account & Buying Group Model: Design and maintain a trusted single view of the account and buying committee. • Lead Measurement & Attribution Strategy: Define and evolve multi-touch attribution models, funnel measurement standards, and closed-loop revenue reporting. • Generate Strategic Insights & Business Recommendations: Translate unified marketing and GTM data into actionable analytical insights. • Drive Cross-Functional Impact & Continuous Improvement: Partner across Marketing, RevOps, Sales, Finance, and Data teams to align systems and processes.