Data Scientist

About the Company

Our client is building the first AI Audience Intelligence platform designed to help marketers identify and activate high-value audiences based on real business context. Backed by Alchemist, Silicon Valley's top B2B accelerator, and already trusted by leading organizations—including a top MLB team—the company is helping sports and event marketers turn fragmented data into clear, actionable decisions.

By combining generative AI with more than 100 proprietary modules, the platform helps teams answer practical, high-impact questions: what offers to send, to whom, when, and with what message. Workflows that traditionally take months are reduced to weeks, with growing momentum across sports, entertainment, and future expansion into fashion and travel.

This is a tight-knit team of builders and problem-solvers tackling a clear gap in marketing intelligence. If you're excited by applied AI, real customer impact, and the chance to shape a product at an early stage of growth, this is an opportunity to work close to the problem and close to the outcome.

Core values: Humility – Always learning. Adaptability – Staying ahead in a fast-moving space. Transparency – Tackling challenges openly as a team. Proactivity – Thinking ahead, pushing boundaries. Authenticity – Be yourself and enjoy the ride.

About the Role

As a Data Scientist, you will play a central role in building and deploying AI/ML models that turn complex marketing, ticketing, and CRM data into predictive insights and measurable business outcomes. You’ll work across product, engineering, and marketing to solve practical problems around customer preferences, buying readiness, channel effectiveness, pricing, attendance, and revenue optimization.

This role is well suited for someone who enjoys moving from messy, multi-source data to production-ready models and stakeholder-facing recommendations. You'll contribute to proprietary AI systems, help accelerate time-to-value from months to weeks or seconds, and work on applied use cases across sports, e-commerce, travel, and live events.

What you’ll do:

Design, build, and optimize machine learning models for predictive analytics, including customer segmentation, churn prediction, revenue forecasting, and personalized offer recommendations. Analyze large-scale datasets from diverse sources (e.g., booking data, loyalty programs, and campaign metrics) to identify patterns in customer behavior and marketing effectiveness. Develop proprietary AI algorithms and integrate them with Customer Data Platforms (CDPs) and CRMs to enable real-time insights and automated campaigns. Collaborate with product, engineering, and marketing teams to assess client needs, write custom code, and deliver tailored AI solutions that address challenges like cart abandonment, pricing strategies, and event attendance optimization. Conduct exploratory data analysis (EDA) and A/B testing to validate model performance and ensure accuracy in targeting (e.g., identifying ideal fans for specific events or demographics). Monitor and refine models for scalability, focusing on speed-to-revenue by reducing deployment times from months to weeks or seconds. Stay ahead of industry trends in AI/ML, contributing to our library of over 100 proprietary modules for applications in live events, travel, and e-commerce. Present insights and recommendations to stakeholders, translating complex data findings into actionable business strategies.

Your background and skills will include:

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field (PhD preferred). 4+ years of experience in data science or machine learning roles, with a proven track record in predictive modeling and analytics. Proficiency in programming languages such as Python or R, and experience with ML frameworks like TensorFlow, PyTorch, scikit-learn, or similar. Strong knowledge of statistical methods, data processing tools (e.g., Pandas, NumPy, SQL), and big data technologies (e.g., Spark, Hadoop). Experience working with marketing or customer data, including integration with CRMs/CDPs and handling unstructured data from sources like reviews or social interactions. Familiarity with AI-driven applications in e-commerce, travel, or entertainment sectors. Excellent problem-solving skills and the ability to work in a collaborative, agile environment. Experience in building AI solutions for revenue optimization, audience intelligence, or personalized marketing. Knowledge of cloud platforms (e.g., AWS, Google Cloud) for model deployment and scaling. Background in domains like sports analytics, event ticketing, or hospitality data. Publications or contributions to open-source AI/ML projects. Ability to handle multilingual or international datasets for global clients.