- Company Name
- Fincons Group
- Job Title
- Enterprise Architect
- Job Description
-
Job Title: Enterprise Architect
Role Summary: Design and implement enterprise‑grade analytics for CBAM risk management, converting policy requirements into reproducible, auditable machine learning models and integrating them into production systems.
Expectations: Deliver end‑to‑end data science solutions (ingestion → model → deployment), uphold model governance, collaborate with cross‑disciplinary teams, and effectively communicate results to non‑technical stakeholders.
Key Responsibilities:
- Design and specify analytical components for CBAM risk workflows.
- Translate CBAM policy into risk‑scoring logic, profiling models, and alert frameworks.
- Define and document data pipelines for ingestion, transformation, risk calculation, and delivery.
- Support the development and deployment of statistical and machine‑learning models for emission anomaly detection and behavioral risk scoring.
- Integrate modeling artifacts into production pipelines, dashboards, and operational interfaces.
- Ensure auditability, reproducibility, and interpretability of risk analytics systems.
- Liaise with policy, architecture, and infrastructure teams to align analytics with business and operational needs.
Required Skills:
- Minimum 6 years of professional experience designing and applying advanced data science models (e.g., fraud detection, emissions modeling, survival analysis, risk classification).
- Proven end‑to‑end model lifecycle experience (data ingestion, validation, deployment, integration).
- Proficiency in Python and R for reproducible analytics; familiarity with RStudio, Anaconda, and version‑controlled development.
- Strong knowledge of machine‑learning techniques (classification, clustering, time‑to‑event), anomaly detection, risk scoring, and bias mitigation.
- Understanding of model governance: auditability, interpretability, reproducibility.
- Ability to communicate technical outcomes to non‑technical stakeholders.
- English language proficiency at B2 level or higher.
Required Education & Certifications:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or related field.
- Certifications in data science or machine‑learning (e.g., Microsoft Azure AI Engineer, AWS ML Specialty, Google Cloud ML Engineer) are a plus.