Senior Quantitative Analyst(Python-Based Forecasting)

Job Description: What you will do • Write clean, correct Python code to analyze time‐series and tabular datasets using Pandas and NumPy. • Implement Monte Carlo simulations to model uncertainty in forecasts and produce confidence intervals (e.g., P10, P50, P90). • Convert existing Excel‐based models or business logic into maintainable Python implementations. • Aggregate, clean, and transform real‐world datasets (CSV or table‐based) to produce forecasting inputs and outputs. • Build notebook‐based analysis that can be re‐run regularly with updated data. • Add basic sensitivity analysis to understand which inputs most affect forecast outcomes. • Work with stakeholders to clarify assumptions and validate results, focusing on correctness, transparency, and reproducibility. Required skills and experience • Strong Python proficiency, including writing functions from scratch and debugging code live. • Strong Pandas experience, including: • groupby and aggregation • joins and merges • time‐based grouping and sorting • handling missing or messy data • Hands‐on experience implementing Monte Carlo simulations in Python , not just describing them conceptually. • Familiarity with NumPy random sampling and percentile calculations. • Experience translating Excel models or analytical logic into Python with validation of results. • Comfortable working in Jupyter notebooks. Nice to have (not required) • Experience working with cloud usage or billing datasets. • Exposure to forecasting, FP&A, capacity planning, or cost modeling. • Experience building models that are refreshed on a regular cadence (weekly or monthly). • Familiarity with basic model versioning or reproducibility patterns. What success looks like • Can take a dataset and produce correct summaries and forecasts without hand‐holding. • Can implement Monte Carlo simulations that run, produce correct distributions, and are explainable. • Writes Python that others can read, rerun, and validate. • Handles live coding and problem‐solving without getting overwhelmed by the environment.