Machine Learning Engineer
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Job Summary
On behalf of our client we are seeking a highly skilled Machine Learning Engineer to join their team in Al Khobar.
The role is responsible for designing developing and productionizing machine learning algorithms for financial intelligence systems with a focus on Cost Variance Cost Forecasting Scenario and What-If Analysis and KPI Variance.
The position combines advanced quantitative data science with robust software engineering covering the full lifecycle of predictive models from mathematical formulation and prototyping to scalable production pipelines.
The role requires strong expertise in machine learning statistical modelling time-series forecasting Python and MLOps with experience in financial economic or operational planning data considered highly relevant.
- Design train and validate advanced machine learning and statistical models for multi-horizon cost forecasting and KPI predictions.
- Apply advanced time-series and sequential modelling techniques to capture seasonal patterns macroeconomic dependencies and trend shifts in financial data.
- Develop simulation engines including Monte Carlo and stress-testing frameworks for interactive What-If scenarios.
- Build automated anomaly detection and diagnostic models to identify the root causes of variance between planned forecasted and actual financial KPIs.
- Refactor prototype code into clean scalable production services.
- Deploy and containerize models orchestrate pipelines and build monitoring systems to detect feature and model drift.
- Partner with corporate finance teams to translate complex statistical outputs into transparent interpretable insights and interactive strategic dashboards.
Required Skills:
Required Skills and Qualifications Proven experience in business analysis including requirements elicitation and documentation. Strong process modeling skills particularly with BPMN. Expertise in use case documentation and translating business needs into structured technical requirements. Excellent communication and stakeholder management skills with the ability to work cross-functionally. Solid understanding of software applications and their operational contexts. Demonstrated ability in designing validation frameworks and structured data templates. Familiarity with knowledge structuring techniques for AI and human collaboration. Experience in developing business logic complexity assessments and prioritization frameworks. Ability to work independently and as part of a multidisciplinary team. Preferred Qualifications Bachelors or Masters degree in Business Analysis Computer Science Information Systems or a related field. Experience working with AI-driven test generation or machine learning projects. Prior involvement in learning teams or knowledge management initiatives. Certification in Business Analysis such as CBAP PMI-PBA or equivalent is a plus.
