Data Scientist (Cost Optimization)

Job description

US Mobile is building the future of wireless communication. The goal: [one unified network](http://usmobile.com/manifesto) open to any person and any device, worldwide. Connection without walls. We’re getting there by empowering customers. All three major networks on one phone and one plan, plus home internet from Starlink. No lock-in. No commitments. Custom fit plans at every price point. 24/7 customer support with real people, empowered to help. We get real-time feedback [from Reddit](https://www.reddit.com/r/USMobile/), surveys, and customer support informing product roadmaps and everything we do. It’s working — we’re [The Wirecutter’s favorite cellular carrier](https://www.nytimes.com/wirecutter/reviews/best-wireless-carrier/), and Consumer Reports has named us [the top-rated mobile carrier](https://usmobile.com/cr) two years in a row.\* And we’re building innovative systems that scale. A network agnostic tech stack. Agile, cross-functional teams built on trust and mutual respect. This work isn’t for everyone. If you work fast, flexibly, and collaboratively — without compromising standards — we want to hear from you. We’re looking for a **\*\*Data Scientist, Cost Optimization\*\*** to own the unit economics of our network costs. You’ll build the models and optimizations that decide the most cost-efficient configuration for every line on our networks, validate those models against real financial data, and turn your analysis into decisions the business acts on. This is decision science more than machine learning — and business judgment matters as much as the math. ### Responsibilities: - Build and run the cost models and optimizations that determine the most efficient plan configuration across our subscriber base. - Validate cost models against carrier invoices and financial data; investigate and resolve discrepancies. - Monitor, forecast, and manage pooled usage and network spend, recommending corrective actions with quantified impact. - Model pricing and contract scenarios on actual usage data to support commercial decision-making. - Move recommendations into production through automated, auditable workflows, and verify outcomes. - Design, build, and maintain the underlying data models using dbt, Redshift, and related tools. - Use AI tooling to accelerate modeling, analysis, SQL/dbt work, and documentation. ### Requirements: - 4+ years of experience in data science, decision science, operations research, pricing/optimization, or cost analytics — ideally where your recommendations carried real financial impact. - Hands-on experience formulating and solving optimization problems (linear programming, cost modeling, marginal-cost analysis, or similar) that informed real business decisions. - Strong business judgment, with experience owning a commercial or cost recommendation end-to-end. - Strong SQL skills, including experience with large datasets, complex transformations, and performance optimization. - Proficiency in Python. - Experience validating analytical models against external financial data (invoices, bills, or settlements). - Demonstrated use of AI in your day-to-day workflow — LLM-assisted coding or prompt-driven data exploration. - Strong communication skills, with a bias toward clear recommendations and measurable business impact. ### Nice to Have: - Telecom, MVNO, or other usage-based/wholesale cost domain experience; cloud cost management (FinOps). - Experience with dbt and a modern orchestrator (Dagster, Airflow, or similar). ### Benefits and Perks: - Competitive Salary - Gym reimbursement - Commute reimbursement - Flexible working hours - Professional development stipend - Flexible time off - Cell phone service (up to $100/mo)