Data Scientist

About CharterUP

Charter

UP is transforming the $30 billion group transportation industry with cutting-edge technology and innovative SaaS software, delivering an industry-leading experience for both customers and operators. Our platform connects users to thousands of charter bus and minibus operators nationwide, with real-time availability, transparent pricing, and detailed vehicle options for corporate events, shuttles, weddings, and more.

With Charter

UP, group transportation is an elevated, reliable experience. Join us as we lead the future of group travel.

• Innovative Impact:
  Be part of the team revolutionizing group travel and setting new standards.
• Growth Opportunities:
  Hyper growth company recognized by Inc.; dynamic, growth-stage organization.
• Driven Team:
  Collaborate with driven tech minds in a remote-first environment with a tech hub in Austin, TX.
• Funding and Stability: $60 million Series A funding with planned expansion and long-term stability.

Charter

UP is seeking a founding Staff Data Scientist to launch and build our data science capabilities. As the first dedicated hire, you7ll design and deploy ML models in production while laying the groundwork for a scalable data science function. Your initial impact will be hands-on, developing and implementing ML models that optimize pricing and availability to shape the customer and operator experience.

Over time, you7ll expand into forecasting, automation, and optimization, establishing the principles, infrastructure, and culture that guide data-informed decision-making across Charter

UP.

This role offers the opportunity to combine immediate technical ownership with the chance to set the foundation for a data-first culture that transforms the future of group mobility.

Title: Staff Data Scientist

Reports to: Chief Product Officer

Location: This position is based in Austin, TX (Hybrid: Monday, Wednesday, Friday in-office).

• Hands-On Model Development: Design, implement, and maintain production ML models with a focus on pricing and availability, expanding into forecasting, automation, and optimization.
• Build and Shape the Function: Establish principles, infrastructure, and systems for data science, ensuring a scalable foundation for long-term growth.
• Data Infrastructure & Quality: Drive improvements in data pipelines, modeling, and governance to ensure reliable, high-quality data for decision-making.
• Strategic Partnering: Collaborate with executives and cross-functional teams to translate data into clear insights, metrics, and recommendations that influence business direction.
• Champion a Data-First Culture: Promote best practices in experimentation, statistical rigor, and data storytelling, while mentoring peers and setting the stage for a future team.

• Translate pricing and availability insights into scalable systems: Work with Engineering to embed elasticity models, demand forecasts, and operator availability logic into the core platform so they directly influence quotes and surfaced options.
• Build production-ready pricing and matching levers: Design and implement dynamic rules or models that optimize both customer price acceptance and operator match rates, ensuring supply is surfaced efficiently and profitably.
• Establish robust testing and monitoring: Put in place frameworks for controlled experiments on pricing and supply-matching, with KPIs balancing margin, conversion, and operator acceptance.
• Accelerate decision-making with transparency: Ensure pricing and availability strategies are explainable and measurable, with dashboards visible across Product, Sales, Finance, and Ops.
• Lay the foundation for scale: Develop processes and systems that allow pricing and operator matching to scale beyond one-off analysis, creating a repeatable, trusted capability.

• Proven Data Science Leadership: 8+ years in data science building and scaling data-driven functions, leading cross-functional teams, and delivering high-impact projects in high-growth or startup environments.
• Machine Learning & Statistical Expertise: Hands-on experience designing, deploying, and maintaining ML models in production, including pricing, demand forecasting, and availability optimization; depth in AI/ML, LLMs, NLP, statistical modeling, experimental design, and advanced analysis.
  Data Infrastructure & Technical Depth: Proficiency with SQL in big data environments, Python/R for large-scale analysis, and experience in data modeling, pipelines, data quality and governance.
• Strategic and Business Alignment: Ability to align data science initiatives with business goals, translating data into clear strategies and actionable insights to drive growth and efficiency.
• Collaboration and Communication: Excellent communicator across technical and non-technical teams; ability to influence at the executive level, mentor peers, and champion a data-first culture.
• Step 1 - Video call:
  Talent Acquisition interview
• Step 3 - Video call:
  Team…