Quantitative Analyst ( Strong Python/Jupyter )

Required 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.