Data Scientist Computer Vision & Financial Intelligence

Erada

Key Responsibilities

• Computer Vision & OCR
• Financing & Risk Use Cases
• Model Development & Deployment
• Data Analysis & Feature Engineering
• Governance & Documentation
• Design and develop computer vision models for document analysis and image-based decisioning.
• Build and optimize OCR pipelines for:
• National IDs, contracts, application forms, and supporting documents.
• Low-quality, mobile-captured, real-world images.
• Implement image preprocessing and enhancement techniques to improve OCR and classification accuracy.
• Work on live / near-real-time image processing use cases when required.
• Apply data science techniques to financing-related problems such as:
• Customer onboarding and document verification.
• Fraud detection and anomaly identification.
• Creditworthiness and risk signal extraction.
• Translate business and regulatory requirements into measurable model outputs.
• Partner closely with risk, product, and engineering teams to ensure models are usable and explainable.
• Build, train, evaluate, and fine-tune ML models with a strong focus on accuracy, robustness, and bias control.
• Prepare models for production deployment, working closely with engineering teams.
• Monitor model performance post-deployment and iterate based on real-world data.
• Analyze structured and unstructured datasets (images, text, metadata).
• Engineer meaningful features from visual and non-visual data sources.
• Validate data quality and identify edge cases early.
• Ensure models align with regulatory, audit, and explainability requirements common in financial services.
• Clearly document methodologies, assumptions, limitations, and results.
• Communicate findings effectively to both technical and non-technical stakeholders.