Data Scientist (Cost Optimization)
$150,000–$200,000 year
On-siteNew York City, New York, United States
Job Summary
Build and run cost models and optimizations to determine efficient plan configurations across the subscriber base. Validate these models against carrier invoices and financial data, investigating discrepancies. Monitor pooled usage and network spend, forecasting trends and recommending corrective actions with quantified impact. Model pricing and contract scenarios on actual usage data to support commercial decisions, then move recommendations into production through automated, auditable workflows. Design, build, and maintain underlying data models using dbt, Redshift, and AI tooling to accelerate analysis and documentation.
Required Qualifications
- 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.
Desired Qualifications
- 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).
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