Quantitative Analyst ( Strong Python/Jupyter )

Required skills and experienceStrong 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 havePrior work in FP&A, cloud economics, FinOps, or cost and usage modeling for AWS, Azure, or GCP. Originally posted on Himalayas