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About the Role

CharterUP is seeking a Staff Data Scientist to build our data science capability from the ground up. Your first mandate is to develop a rigorous, ground-truth understanding of our pricing and marketplace dynamics, partnering closely with Engineering on the data foundation needed to support this work. As that foundation matures, you'll expand into experimentation, model development, and production ML, while helping build the systems and standards that let data science scale across the company.

Title: Staff Data Scientist

Reports to: Chief Product Officer

Location: Remote, US

What You'll Do

• Hands-On Model Development: Lead driver analysis and data quality work to establish the foundation for machine learning model development.
• Build and Shape the Function: Establish the principles, infrastructure, and systems for data science, ensuring a scalable foundation that supports 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 closely with executives and cross-functional teams to translate complex 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.

Key Initial Objectives (6-12 months)

• Establish a rigorous analytical baseline on pricing and marketplace economics, in partnership with the Pricing and Availability teams.
• Partner with our new data engineer and the team leading our Snowflake migration to define what "ready" data looks like, and help prioritize that work.
• Establish shared metrics and data definitions that other data functions across the company (Finance, Revenue) can also adopt.
• Deliver findings that directly inform our pricing roadmap and CEO-visible pricing initiatives.
• Lay groundwork for future experimentation and ML, without committing to production timelines this year.

What You'll Bring

• Data Science Leadership: 8+ years of experience in data science with a track record of leading high-impact initiatives and influencing cross-functional teams in high-growth or startup environments.
• Machine Learning & Statistical Expertise: Experience applying machine learning, statistical modeling, and experimentation to solve complex business problems, ideally in pricing, forecasting, optimization, or marketplace environments. Hands-on experience designing, deploying, and maintaining production ML models is a plus, as is familiarity with AI/ML, LLMs, and NLP.
• Technical Expertise: Advanced proficiency in SQL and Python or R, with experience working in large-scale data environments and building reliable, high-quality datasets for analytics and machine learning.
• Business Acumen: Demonstrated ability to translate complex data into actionable insights that influence strategy, improve decision-making, and drive measurable business outcomes.
• Cross-Functional Collaboration: Excellent communication and partnership skills, with the ability to influence technical and non-technical stakeholders and collaborate effectively across Product, Engineering, and business teams.
• Navigating Ambiguity: Comfortable working with incomplete, messy, or unstructured data, bringing structure to ambiguous problems and delivering practical, data-driven solutions.

Recruiting Process

• Step 1 - Video call: Talent Acquisition interview
• Step 2 - Video call: Hiring Manager interview
• Step 3 - Video call: Team interviews (x3)
• Step 4 - Video call: Case Study & Panel Presentation
• Step 5 - Offer & reference check
• Welcome aboard!