Senior Machine Learning Engineer (Financial Forecasting / FP&A)
Type: Full-time
Location- Remote
Experience- 5+ years
About the role
We are hiring a Senior Machine Learning Engineer to build a driver-based OPEX forecasting and scenario planning capability within a large-scale analytics programme. You will replace static, spreadsheet-based budgeting with ML models that link operating costs to real operational drivers, and power a what-if scenario engine used directly by finance and operations leaders.
What you'll do
- Engineer cost-driver features from financial and operational data: headcount, activity rates, maintenance cycles, workforce deployment, occupancy, and seasonal variables
- Develop, validate, and deploy regression/ensemble forecasting models on Databricks predicting OPEX by cost category, business unit, and planning horizon, against a defined MAPE acceptance target
- Embed SHAP explainability so every forecast and scenario delta is attributable to named drivers
- Build the modelling layer behind a scenario planning engine: parameterised what-if runs with explainable scenario comparisons
- Implement MLOps: MLflow tracking, CI/CD deployment, drift monitoring, documented retraining
- Work directly with finance stakeholders to define driver sensitivities, validate outputs against actuals, and support UAT
What you'll need
- 5+ years of ML engineering experience, with demonstrable delivery of forecasting or financial modelling systems into production
- Strong grounding in driver-based/regression forecasting, ensemble methods, and forecast accuracy evaluation (MAPE and alternatives)
- Hands-on SHAP (or equivalent) explainability experience
- Strong Python; production Databricks and MLflow experience
- Ability to speak the language of finance: budgets, actuals, variance, cost centres, planning cycles
Nice to have
- Databricks certification (certification support provided)
- Experience with FP&A, EPM, or planning platform ecosystems (SAP, Oracle)
- Experience building simulation or scenario tools for business users
- Prior delivery experience in the GCC region
Interested candidates share their resume at [Confidential Information]
