Senior Quantitative Analyst, Cloud Cost Forecasting & Modeling

Duration: 6+ months Location: 100% REMOTE Requirements: • Strong Python + Jupyter Notebook experience (heavy Pandas usage) • Experience converting complex Excel models into Python (formula tracing, validation) • Hands-on Monte Carlo simulation (P10/P50/P90, distributions, scenario modeling) • Experience with cloud cost modeling (AWS, Azure, GCP - compute, storage, networking) • Strong SQL for data extraction and analysis • Experience building lightweight data pipelines (APIs, files, DB queries) • FP&A-style forecasting, variance analysis, and driver-based modeling • Experience with data validation, auditability, and versioning of model runs • Ability to explain outputs and variance drivers to non-technical stakeholders Key Responsibilities: • Rebuild Excel-based cloud cost model into Python (Jupyter notebooks) • Create automated data pipelines and clean Pandas datasets for modeling • Build parameterized forecasting engine across cloud cost drivers • Implement Monte Carlo simulations for probabilistic forecasting • Develop variance analysis (actual vs forecast, forecast vs forecast) • Deliver sensitivity analysis, scenario modeling, and driver ranking • Build notebook-based visualizations (waterfalls, fan charts, etc.) • Ensure full auditability and version control of model inputs/outputs • Partner with FinOps, FP&A, Data Engineering, and Infrastructure teams Nice to Have: • Experience in FinOps, cloud economics, or cost modeling • Familiarity with Airflow, Prefect, dbt, or scheduling tools • Experience with Plotly, Matplotlib, or Bokeh • Exposure to PyMC, NumPyro, or probabilistic modeling tools 26-00317 Apply Now Apply Now