Senior Data Scientist

Major League Soccer’s Strategy and Business Intelligence group is tasked with supporting strategic decision making and resource allocation across the League – with a focus on driving fan growth, revenue capture, and operating efficiencies – by providing impactful data driven insights, analysis, and recommendations . We are looking for a Senior Data Scientist to build and own advanced machine learning models that drive fan growth, engagement, and revenue across the League. This is a highly technical, hands-on role where you will spend the majority of your time working in code, developing models, and solving complex data problems. You will work with large-scale fan and marketing datasets to power segmentation, personalization, and predictive insights that directly influence business strategy. If you are someone who enjoys going deep on data, building models end-to-end, and seeing your work deployed into real-world applications, this role offers a unique opportunity to have visible impact at scale. Responsibilities • Build and deploy machine learning models across segmentation, forecasting, recommendation, and classification use cases • Own the full model lifecycle including data exploration, feature engineering, training, validation, production deployment and impact analysis • Develop customer segmentation and clustering models to optimize fan growth and engagement • Design and implement personalization and “next best action” models • Lead modeling efforts for media mix and marketing performance optimization • Partner with Data Engineering to productionize models and integrate outputs into downstream systems • Work closely with internal stakeholders to translate model outputs into actionable insights Required Skills And Experience • Strong hands-on experience building and deploying machine learning models in Python • Deep expertise in SQL and processing large-scale datasets in cloud environments, including distributed compute with Spark/ PySpark (EMR) and developing robust, scalable batch data pipelines • Experience with core Python data and ML libraries, including NumPy, pandas, and scikitlearn • Experience applying a range of machine learning techniques, including regression, decision trees and ensemble methods (e.g., XGBoost , LightGBM ), clustering, causal inference, and recommendation systems • Experience with ML/data engineering infrastructure and distributed processing frameworks • (e.g., Airflow, AWS SageMaker, EMR, PySpark ) to build, orchestrate, and scale end-to-end ML pipelines • Experience with experimental design and measurement, including hypothesis testing, A/B and multivariate testing, and causal inference, with the ability to design, analyze, and interpret controlled experiments • Experience with applied AI systems, including developing and deploying agentic workflows, applying techniques such as retrieval-augmented generation (RAG), fine-tuning, and prompt engineering • Experience contributing to the design of conversational and semantic layers to ensure accurate , reliable outputs • Strong communication and collaboration skills. • Strong interpersonal skills and the ability to effectively communicate, both verbally and in writing • Demonstrated decision making and problem-solving skills. • High attention to detail with the ability to multi-task and meet deadlines with minimal supervision • Proficiency in Word, Excel, PowerPoint and Outlook. What Makes This Role Different • Builder-first role : This role is primarily focused on coding, modeling, and deploying solutions. While dashboarding and reporting may be part of the work, the core emphasis is on building and delivering data-driven models. • Real-world impact: Your models will directly influence fan engagement, marketing strategy, and revenue outcomes • High ownership: You will take over key modeling areas and evolve them beyond current vendor-supported solutions • Fast-paced environment: You will operate in a high-expectation environment with meaningful deadlines and visibility Qualifications • Bachelor’s Degree required • 8+ years of experience required Total Rewards Major League Soccer offers a competitive starting base salary of $130,000 - $150,000, based on individual qualifications, market financials , and operational business needs. We are committed to providing a Total Rewards package that attracts, supports, engages, and retains talent. Our benefits package includes comprehensive medical, dental, and vision coverage, a $500 wellness reimbursement, and generous Holiday and PTO schedule to promote work-life balance. We also prioritize career and professional development, offering o