United States onlyRequired skills and experience
- Strong Python and Jupyter notebook experience with heavy use of Pandas for joining, reshaping, aggregating, and validating multiple data frames. Experience with NumPy and SciPy statistics is highly preferred.
- Hands on experience building Monte Carlo simulations including distribution selection and fitting, sampling design, and interpreting P10 P50 P90 results. Experience handling correlated variables is a plus.
- Experience converting complex Excel models into code by tracing formulas, documenting assumptions, and validating numeric accuracy.
- Ability to build reliable data pipelines in Python including API authentication, pagination, schema normalization, error handling, and incremental refresh.
- Strong SQL skills for extracting inputs from data warehouses or billing databases.
- Experience with versioning and auditability beyond Git, including structured snapshot storage of inputs and outputs.
- Comfort explaining model outputs and variance drivers to non-technical stakeholders and producing business ready commentary.
Nice to have
- Prior work in FP&A, cloud economics, FinOps, or cost and usage modeling for AWS, Azure, or GCP.
